US7369691B2 - Processor for analyzing tubular structure such as blood vessels - Google Patents
Processor for analyzing tubular structure such as blood vessels Download PDFInfo
- Publication number
- US7369691B2 US7369691B2 US10/803,930 US80393004A US7369691B2 US 7369691 B2 US7369691 B2 US 7369691B2 US 80393004 A US80393004 A US 80393004A US 7369691 B2 US7369691 B2 US 7369691B2
- Authority
- US
- United States
- Prior art keywords
- image
- center line
- data
- vessel
- unit configured
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related, expires
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/08—Volume rendering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/12—Edge-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30172—Centreline of tubular or elongated structure
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2215/00—Indexing scheme for image rendering
- G06T2215/06—Curved planar reformation of 3D line structures
Definitions
- the present invention relates to a processor for analyzing a tubular structure. More particularly, the present invention relates to a processor for analyzing a tubular structure which permits three-dimensional observation, in a diagnostically useful manner, of a tubular structure (system) such as blood vessels, the intestine, the windpipe, and the esophagus on the basis of three-dimensional imaging data of a patient captured by a diagnostic medical imaging apparatus (medical modality), and quantitative analysis of indices useful for diagnosis, including the thickness (including local changes such as stenoses and lumps) or the length of a tubular structure.
- a tubular structure system
- a diagnostic medical imaging apparatus medical modality
- quantitative analysis of indices useful for diagnosis including the thickness (including local changes such as stenoses and lumps) or the length of a tubular structure.
- X-ray angiographic tests require arterial injection of an angiographic agent
- three-dimensional imaging of blood vessels using X-ray CT or MRI permits angiography of blood vessels by venous injection.
- Venous injection is less invasive and can alleviate the burden on patients.
- X-ray imaging is two-dimensional
- assessment of a topological abnormality based on this imaging is limited.
- the diagnosis tends to underestimate the degree of blood vessel stenosis.
- Use of three-dimensional imaging permits observation of a three-dimensional form, thus improving the accuracy of diagnosis of the stenosis.
- Three-dimensional imaging is also effective for identifying the three-dimensional structure of the blood vessel or an aneurysm.
- X-ray angiographic imaging at present is inadequate at rendering capillaries.
- the scope of application of diagnosis using three-dimensional images will be expanded.
- Japanese Examined Patent Application Publication No. 3-10985 discloses a method for calculating the longitudinal vector of a tubular structure taken from three-dimensional imaging data derived from X-ray CT, MRI, and ultrasonic diagnostic apparatuses by means of a “vector detector”, calculating sections perpendicular to the tubular structure from the resultant longitudinal vector, and preparing and displaying images cut along these sections.
- U.S. Pat. No. 5,891,030 discloses a method comprising the steps of extracting a center line of a tubular structure from an image of the tubular structure in a captured three-dimensional image; unbending the tubular structure along this center line in the longitudinal direction thereof into a stretched shape; displaying the stretched image; and displaying a volume-rendering image and a planar reformatted image corresponding to the former image.
- Japanese Unexamined Patent Application Publication No. 2001-175847 discloses a method of producing MPR (Multiplanar Reconstruction) image data of a sectional surface perpendicular to the center line (center line, for example) of an extracted blood vessel, in sequence at positions along the center line of the blood vessel, and displaying the sequential images as an animation.
- MPR Multiplanar Reconstruction
- the area or diameter of the blood vessel can be determined for the individual positions along the blood vessel center line by extracting the center line and the contours of the blood vessel.
- This paper also presents a graph with the blood vessel diameter as the ordinate and the distance along the blood vessel center line as the abscissa.
- the stenosis ratio of a blood vessel is calculated using a reference blood vessel diameter A on the assumption of the absence of stenosis, and the actual diameter B of the stenosis site in accordance with the formula: [100 ⁇ (1 ⁇ (B/A))] (%).
- a method of determining the reference diameter should be needed.
- An example of this calculation method is disclosed in Japanese Unexamined Patent Application Publication No. 5-264232, which comprises the steps of estimating the reference diameter of a blood vessel from an angiographic image taken by a conventional two-dimensional X-ray imaging system, and calculating the stenosis ratio therefrom.
- a tubular structure such as a blood vessel has a complex shape because of the generally complex three-dimensional complex path, it is difficult to identify the position or the state of a disease such as stenoses and lumps even when observing a pseudo-three-dimensional displayed image (such as a volume-rendering image).
- a pseudo-three-dimensional displayed image such as a volume-rendering image.
- Vascular diseases include aneurysm in which the blood vessel suffers from lumps.
- the maximum diameter exceeds, for example, 5 mm, or the secular change in the maximum diameter exceeds, for example, 3 mm/year, the aneurysm may burst. It is generally believed that the patient should receive surgery. In the present circumstances, however, the maximum diameter of the aneurysm is observed and measured by use of an axial image. It is therefore difficult to grasp the three-dimensional shape or the secular change in diameter of the aneurysm, and the results are thus largely dependent upon the diagnostic ability and experience of the physician.
- the present invention was developed in view of the various problems in the conventional observing and analyzing methods of a tubular structure (tubular system) as described above, and has a main object to provide a processor for analyzing a tubular structure that permits easy grasping of the entire and partial three-dimensional shape of a tubular structure such as blood vessel in a patient, that makes it possible to easily find and observe the position or the state of a site to be observed such as a diseased site of stenoses or lumps, and that substantially alleviates the operational burden imposed on the operator who conducts diagnosis and observation, thereby enabling the operating efficiency to be improved.
- the analyzer of a tubular structure of the present invention is provided, as one aspect, as an analyzer analyzing a tubular structure of an object to be examined.
- This analyzer comprises a preparing unit configured to prepare a plurality of sets of three-dimensional image data of the same object examined; a structure extracting unit configured to extract image data indicative of a three-dimensional tubular structure, set by set, from the plurality of sets of three-dimensional image data, thereby a plurality of sets of structure image data being produced; a reference direction specifying unit configured to specify a reference direction to the plurality of sets of three-dimensional image data; a reference point specifying unit configured to specify a reference point to each center line of the tubular structure contained in each of the plurality of sets of structure image data; a stretched image producing unit configured to produce, from each of the plurality of sets of structure image data, data of a stretched image of the tubular structure in each of plural sections which are mutually the same with regard to three-dimensional positions thereof and determined based on the reference direction, thereby
- the stretched image producing unit comprises a contour data extracting unit configured to extract contour data of the tubular structure from each of the plurality of sets of structure image data by using the center line as a reference.
- the analyzer further comprises a contour displaying unit configured to display the contour data of the plurality of sets of contour data of the tubular structure; a change-information acquiring unit configured to acquire information in relation to time-lapse changes of the tubular structure on the basis of the contours of a plurality of tubular structures displayed by the contour displaying unit; and an information displaying unit configured to display the acquired information in relation to the time-lapse changes.
- an analyzer analyzing a tubular structure of an object to be examined.
- This analyzer comprise a preparing unit configured to prepare three-dimensional image data of the same object examined; an image data producing unit configured to produce, from the three-dimensional image data, data of at least one of a volume rendering image of the object, a maximum intensity projection (MIP) image of the three-dimensional image data, a flat reformatted image at an arbitrary section in the three-dimensional image data; a curved reformatted image producing unit configured to produce data of a curved reformatted image from the three-dimensional image data; a center line producing unit configured to produce three-dimensional position data of a center line of the tubular structure by using the three-dimensional image data; a reference image displaying unit configured to display the center line by overlaying the position data of the center line on data of a reference image consisting of one of the volume rendering image, the maximum intensity projection (MIP) image, the flat reformatted image, and the curved reformatted image; a curved
- the analyzer further comprises an analysis unit configured to analyze a morphological feature of the tubular structure; a reception unit configured to receive a signal indicating whether or not the position of the center line displayed on both the reference image and the curved reformatted image is acceptable; and an analysis permitting unit configured to permit the analysis unit to analyze the morphological feature of the tubular structure only when the signal received by the reception unit indicates that the position of the center line is acceptable.
- an analyzer analyzing a tubular structure of an object to be examined.
- This analyzer comprises a preparing unit configured to prepare three-dimensional image data of the same object examined; an image data producing unit configured to produce, from the three-dimensional image data, as data of a reference image, data of at least one of a volume rendering image of the object, a maximum intensity projection (MIP) image of the three-dimensional image data, a flat reformatted image at an arbitrary section in the three-dimensional image data; a unit configured to produce data of a center line indicating three-dimensional positional information of the tubular structure, from the three-dimensional image data; a unit configured to produce data of either a stretched image or a perpendicular sectional image of the tubular structure on the basis of the data of the center line; a unit configured to use the data of the reference image, the either stretched image or the perpendicular sectional image, and the center line so that the reverence image with the center line overlaid thereon and either the stretched image
- FIG. 1 is a block diagram illustrating a typical hardware configuration adopted in various embodiments of the processor for analyzing a tubular structure of the present invention
- FIG. 2 is a rough flowchart illustrating an outline of the processing for display and analysis of a tubular structure, such as a blood vessel, executed in the first embodiment
- FIGS. 3A and 3B illustrate examples of display on the screen
- FIG. 4 is a flowchart illustrating an outline of the processing of interlocking display resulting from correction of the center line position
- FIG. 5 illustrates a screen showing the interlocking display resulting from correction of the center line position
- FIG. 6 illustrates a screen showing the interlocking display resulting from correction of the center line position
- FIG. 7 is a descriptive view of a window for accepting correction of the center line position
- FIGS. 8A to 8C illustrate screens showing examples of the display of extracted blood vessel walls
- FIGS. 9A and 9B illustrate screens for explaining correction of the contour of the vessel
- FIG. 10 illustrates an example of the display of a blood vessel image
- FIG. 11 illustrates an example of the display of the result of analysis of a vessel
- FIG. 12 illustrates another example of the display of the result of analysis of a vessel
- FIG. 13 illustrates still another example of the display of the result of analysis of a vessel
- FIG. 14 illustrates yet another example of display of the result of analysis of a vessel
- FIGS. 15A to 15C illustrate screens for explaining an example of facilitation of orientation in a first variation of the first embodiment
- FIGS. 16A and 16B illustrate screens for explaining an example of facilitation of orientation in the first variation
- FIG. 17 illustrates a screen used for explaining an interlocking display applicable to the first variation
- FIGS. 18A and 18B illustrate other screens used for explaining an interlocking display applicable to the first variation
- FIG. 19 is a flowchart for explaining an outline of processing of the interlocking display in a second variation of the first embodiment
- FIG. 20 illustrates a screen for explaining the interlocking display in the second variation
- FIGS. 21A and 21B are schematic views of a blood vessel for explaining the necessity to add a center line in a third variation of the first embodiment
- FIG. 22 is a schematic flowchart illustrating the correction processing of the center line corresponding to addition and displacement of passage points in the third variation
- FIGS. 23A and 23B are schematic views of blood vessel for explaining the addition of passage points in the third variation
- FIG. 24 is a functional block diagram for explaining a second embodiment of the analyzing processor of a tubular structure of the present invention.
- FIG. 25 illustrates the straight volume preparation processing executed in the second embodiment
- FIG. 26 illustrates a change in sectional position of the straight view and the perpendicular view, executed in the second embodiment
- FIG. 27 illustrates the correction processing of the contour extracted from the tubular structure, executed in the second embodiment
- FIG. 28 illustrates the preparation processing of a parametric image executed in the second embodiment
- FIG. 29 illustrates an example of the default image (monitor screen) displayed in the second embodiment
- FIG. 30 illustrates the display of a specific-area three-dimensional image, executed in the second embodiment
- FIG. 31 illustrates the volume data display executed in the second embodiment and the parametric display in the specific-area three-dimensional display
- FIG. 32 illustrates preparation of a hypothetical tubular structure model in a normal state in the second embodiment
- FIG. 33 is a rough flowchart explaining an outline of the display and quantitative analysis of a tubular structure, such as a blood vessel, executed in the second embodiment;
- FIG. 34 is a functional block diagram for explaining a third embodiment of the processor for analyzing a tubular structure of the present invention.
- FIG. 35 illustrates positional alignment processing executed in the third embodiment
- FIG. 36 illustrates the calculation of the secular change executed in the third embodiment
- FIG. 37 illustrates preparation of a secular change image executed in the third embodiment
- FIG. 38 illustrates a screen for showing a typical measuring range setting screen displayed in the third embodiment
- FIG. 39 illustrates a screen for showing a typical secular change observation screen displayed in the third embodiment.
- FIG. 40 is a rough flowchart explaining an outline of the processing for observing the secular change of a tubular structure, such as a blood vessel, executed in the third embodiment.
- This image processor functions as the analyzer according to the present invention.
- FIGS. 1 to 14 A first embodiment will be described with reference to FIGS. 1 to 14 .
- the image processor of this embodiment is provided as a computer device connected online to a medical modality via a communication line as a computer device incorporated integrally with the medical modality, or as an offline computer device separately from the medical modality.
- this computer device comprises an image processor 11 including a CPU and a memory, a memory unit 12 storing programs and processed data, a display unit 13 , and an input unit 14 .
- the computer device has a function of performing data communication with outside as required.
- Three-dimensional (solid-body) image data of a subject collected by a diagnostic imaging apparatus such as an X-ray CT scanner or an MRI, are sent online or offline to the memory unit 12 .
- These three-dimensional image data are stored in a large-capacity memory medium, such as a magneto-optical disk, provided in the memory unit.
- the image processor 11 therefore includes a CPU 111 .
- the program is read out, and processing for the three-dimensional display/analysis method is sequentially executed in accordance with the procedure described in the program.
- images related with the three-dimensional display/analysis method are displayed on the display unit 13 , and operational information concerning the three-dimensional display/analysis method is received from the operator via the input unit 14 .
- the image processor 11 , the display unit 13 , and the input unit 14 can also serve as interfaces for executing processing of automatic vessel extraction by the operator.
- a processing method and a quantitative analyzing technique for effectively observing the form of a blood vessel on the basis of a three-dimensional image of the vessel photographed by using the angiographic CT/MRI.
- Image data incorporating the blood vessel to be analyzed by a diagnostic medical imaging apparatus are collected, or three-dimensional image data previously collected in this manner are read in.
- a three-dimensional or two-dimensional reference image is prepared from the three-dimensional image data, and this is displayed as a primary screen (primary window) (step S 1 ).
- This reference image can be categorized as at least one of the following kinds of image: a volume rendering image, an MPR image (a flat reformatted image or a curved reformatted image (curved MPR image) on an arbitrary sectional surface), and an MIP (maximum value projection) image.
- the image data are three-dimensional image data taken over a certain distance in the body axis direction by the use of the helical CT technique.
- Image data of a different kind are acceptable as long as they are three-dimensional image data containing the vessel to be analyzed.
- the image data are typically images (sliced images) of body-axis sections, each comprising 512 ⁇ 512 pixels, photographed at intervals of about 2 mm and numbering about 200 images.
- a vessel extracting range is specified (step S 2 ).
- the operator sets 200 sliced images to be sequentially displayed.
- One point in the tubular area on the displayed sliced image is specified by means of a pointing device such as a mouse, and one point on the three-dimensional space is selected from the information of the thus once specified position.
- This operation is carried out twice, once for the starting point S and once for the end point E, and three-dimensional coordinates ps and pe are set, respectively.
- the center line of the tubular area connecting the starting point S and the end point E of the vessel extraction range is extracted (step S 3 ).
- Extraction of the center line can be accomplished by applying three-dimensional line-refining processing to the binarized data derived from extraction of the tubular area within the vessel. More specifically, a technique known as the thinning method or the skeletonization method is applicable (for example, see Ali Shahrokni et al. “Fast skeletonization algorithm for 3-D elongated objects”, Proceedings of SPIE, vol., 4322, pp. 323-330, 2001). A different method for determining the center line of a tubular area is disclosed in U.S. Pat. No.
- FIGS. 3A and 3B illustrate an example of the screen display.
- the flat reformatted image (see FIG. 3A ) is a sectional view of a three-dimensional image on a plane directed toward an arbitrary direction, represented by a grey scale.
- the vessel lumen is represented by a collection of dots for simplicity. While portions other than the vessel are also indicated by a grey scale, all portions are shown in white in FIG. 3A .
- a thick solid line SL represents the extracted vessel center line. Since the vessel center line SL is expressed as a three-dimensional curve, it is not on the same section as that of the flat reformatted image in general. It is, however, displayed in superposition as a curve projected onto this plane.
- the square mark MK shown on the thick solid line SL represents a control point for manually correcting the curve. The curve shape can be corrected by moving this point by operating the mouse or the like.
- the curved reformatted image (see FIG. 3A ) is an image obtained by enlarging, over a two-dimensional plane, a grey scale image resulting from cutting of the three-dimensional image by a curved surface expressed as a collection of straight lines perpendicular to the plane of the flat reformatted image, while passing through the points on the center line (thick solid line MK) of the flat reformatted image.
- the vessel lumen IB is expressed by a collection of dots in FIG. 3B .
- the whole range of the blood vessel is not always displayed in the image if the vessel is three-dimensionally curved.
- the vessel center line SL passes through the vessel interior, the whole range of the vessel for which the center line SL is defined must be depicted in the curved reformatted image if the three-dimensional position of the center line is proper. Information on the thickness or the like is therefore available throughout the whole range of the vessel by observing the curved reformatted image.
- the curved reformatted image is thus effective for observing tomographic information of the blood vessel.
- the vessel center line (thick solid line) SL and the control point MK for manually correcting the center line SL are displayed also in the curved reformatted image.
- the center line position can be three-dimensionally corrected by correcting the position of the control point MK.
- FIG. 4 An outline of the subroutine processing is illustrated in FIG. 4 .
- a reference image and a confirmation image are displayed in parallel on the screen of the display unit 13 .
- the reference image is any of a volume rendering image, an MIP image, a flat reformatted image, and a curved reformatted image.
- the image is a flat reformatted image.
- a curved reformatted image is displayed as a confirmation image. Therefore, the monitor screen shown in FIG. 5 is provided on the display unit 13 .
- the same vessel lumen IB i.e., the image of the blood vessel
- the vessel center line SL is displayed in weight units, along the lumen thereof. Since, at the center portion in the length direction of the flat reformatted image, the position of the extracted center line SL in the lumen width direction is not satisfactory, the vessel lumen IB partially becomes scratchy and disappears at the center portion A corresponding to the length direction of the curved reformatted image. In other words, the operator who observes this image would immediately realize the necessity to correct the position of the vessel center line SL.
- the operator corrects the position of the center line in the flat reformatted image on the monitor screen shown in FIG. 6 by “dragging the center line” by operating the input unit 14 ( FIG. 4 , step S 100 ). For example, as shown by the imaginary arrow AR, the position is moved from the dotted line to the solid line.
- the image processor 22 reads in the positional information of the center line SL resulting from this displacement (step S 101 ), and regenerates the data of the corrected curved reformatted image (step S 102 ).
- the curved reformatted image on the monitor screen displayed currently on the display unit 13 is updated by the use of the thus regenerated data (step S 103 ).
- the vessel lumen IB properly appears on the curved reformatted image, and the center line SL is reliably positioned substantially at the center position in the width direction thereof.
- the “correction and acknowledgement” windows of the “extraction result of the vessel center line” are simultaneously displayed on the monitor screen.
- the operator therefore presses an “accept” button or a “cancel” button on the “correction and acknowledgement” windows by operating the input unit 14 .
- the image processor 11 reads in the signal showing “whether or not the center line position is OKed (acceptable or not)” by the operator and makes such a determination from the operating unit 13 (step S 104 ).
- the determination is NO, i.e., when the center line position is not accepted, the image processor further reads in a signal showing “whether or not the center line correction processing is to be canceled” given by the operator from the operating unit 13 , and makes such a determination (step S 105 ).
- step S 106 When cancellation of the center line correction processing is determined, the image processor 11 resets the monitor display to that before the series of corrections, and sets a flag representing the cancellation (step S 106 ).
- step S 107 when the determination in step S 104 is YES, i.e., when the result of correction of the center line is determined to be acceptable, the image processor 11 performs a prescribed accept processing (step S 107 ).
- This accept processing includes setting a flag representing acceptance of the result.
- the analysis processing of the vessel shape and display of its results (steps S 8 to S 13 ), which will be described later, is permitted only when this flag is set.
- the operator has a chance to visually confirm whether or not the status of the center line position is proper and to correct the same as required.
- the center line position can be manually corrected.
- the curved reformatted image is also automatically corrected substantially in a real-time manner. This ensures proper drawing of the blood vessel (lumen) throughout the entire range of the center line definition in the curved reformatted image, thus making it possible to correct the center line while properly grasping the vessel form. It is therefore possible to more rapidly carry out the correcting operation.
- analysis of the vessel form described later is permitted only when the result of correction of the center line is reasonable. It is therefore possible to further increase the reliability of the result of analysis.
- step S 5 three-dimensional data of the vessel contour, i.e., of the vessel surface shape are extracted (step S 5 ).
- This extraction is executed by using, for example, the technique disclosed in the reference mentioned in the section of the prior art “Onno Wink et al., “Fast delineation and visualization of vessels in 3-D angiographic images”, IEEE Trans. Med. Imag., vol. 19, no. 4, 337-346, 2000”.
- the shape of the vessel contours at the vessel sections (sections substantially perpendicular to the vessel center line) corresponding to points in a finite number on the vessel core is available as positional information of points in the finite number on the contour.
- a three-dimensional curved surface can be defined.
- the thus defined curved surface represents a three-dimensional shape of the blood vessel surface.
- the shape of the vessel contour made available as above is displaced on the monitor, and pieces of positional information in a finite number on the contour thereof can be corrected in response to operator's operation, as in the case of correction of the center line position as required (step S 6 ).
- the shape of the vessel surface determined through the above-mentioned extraction of the vessel contour is displayed in superposition as a contour line over the above-mentioned flat reformatted image and curved reformatted image as shown in FIGS. 8A to 8C (step S 7 ).
- the contour line is a line representing crossing of a three-dimensional vessel surface with a flat plane of a flat reformatted image and a curved surface of a curved reformatted image. Calculation and display thereof are accomplished by repeating, throughout the entire curved surface, a processing of determining and displaying local lines of intersection of local curved surfaces of the vessel surface represented by control points and the surface of the reformatted image. Examples in which the vessel wall is displayed on the flat reformatted image and a curved reformatted image are illustrated in FIGS. 8A to 8C .
- the method for preparing a flat reformatted image and a curved reformatted image is the same as in the case of displaying the center line.
- the curved reformatted image A is a result of spreading along a flat plane and display of a curved surface expressed as a collection of straight lines passing through points on the center line in parallel with the flat plane of a flat reformatted image and a grey scale image of a three-dimensional image cross-section.
- the vessel center line (thin solid line) SL and the contour line (line of intersection of the vessel wall and a curved surface) CT are displayed in superposition thereover.
- Control points (squares) MK for curved surface shape correction are displayed on the contour lines of the curved reformatted images A and B.
- the curved surface shape (vessel surface shape) can be corrected by moving the position of the control point MK by means of a pointing device such as a mouse. Examples of this correction are illustrated in FIGS. 9A and 9 B, respectively.
- the displayed curved surface shape is confirmation by the operator, and if it is determined to be proper, the operator clicks the “confirmation” button.
- the “confirmation” button is pressed, the displayed contour shape is established and used for the subsequent analyzing processing.
- the contour shape is never used for the subsequent processing. This ensures output of the highly accurate result of analysis.
- the extracted blood vessel is displayed (step S 7 ).
- This display of the vessel is carried out by displaying a perpendicular sectional image on the perpendicular view (screen), and displaying an extracted image of the vessel on the straight view (screen).
- the vessel center line When the vessel center line is extracted, it becomes possible to define a section perpendicular to the center line at each point on the center line. This permits display of a flat reformatted image on this surface as a perpendicular sectional image (see FIG. 10B ). Particularly, the image processor 11 prepares, in a real-time manner, and displays, upon each change in section to be displayed along the center line, a corresponding perpendicular sectional image. This is useful for determining the three-dimensional structure of blood vessel such as stenosis.
- the image processor 11 prepares the above-mentioned perpendicular sectional images at slight intervals on the center line, and a three-dimensional volume image is prepared by piling up these images.
- a volume image extended volume image
- the vessel center line corresponds to a particular position (at the center, for example) of the thus prepared perpendicular sectional image.
- the vessel center line forms a straight line. Planes within the extended volume image substantially in parallel with this straight line are set, and a flat reformatted image is prepared from these planes. This leads to preparation and display of a vessel stretched image having a center line of vessel extending straight (see FIG. 10A ).
- the vessel stretched image clearly showing changes in shape such as thickness in the axial direction of the vessel, is useful for observing the three-dimensional shape of the blood vessel from a point of view different from the perpendicular sectional image. Therefore, display of combinations of the perpendicular image and the vessel stretched image as shown in FIGS. 10A and 10B is particularly useful.
- the area BV in FIG. 10 represents an area of blood vessel in the prepared reformatted image.
- the thick broken line VW represents the shape of the extracted vessel wall by means of curves of intersection of the planes having prepared the reformatted images and the vessel wall.
- the longitudinal line L 1 on the vessel stretched image is a cursor indicating the position of the section displayed on the perpendicular sectional image, which can be moved to the right or left on the screen in response to the operators operation.
- the image processor 11 draws again the corresponding perpendicular sectional image in a real-time manner on the perpendicular view.
- the diagonal line L 2 on the perpendicular sectional image is a cursor indicating a section of the vessel stretched image which is similarly rotatable by user's operation.
- the image processor 11 draws again the corresponding section in a real-time manner on the straight view.
- Both ends of the cursors L 1 and L 2 serve as click points, and dragging these points with a mouse permits displacement of the cursor.
- the triangles provided near the cursors L 1 and L 2 are symbols showing in what direction relative to the image the section is viewed.
- the applicable method is not limited to the above-mentioned one which comprises the steps of intermediately preparing an extended volume as described above, and preparing a vessel stretched image by the use of the flat reformatting technique.
- the vessel stretched image can be prepared directly from an extracted vessel center line. The details of this vessel stretched image preparing method will be described later.
- the image processor 11 can switch over the operation, as required, from the display state of vessel extension to an MIP (maximum value projection) image based on the flat reformatted image.
- MIP maximum value projection
- the analyzing processing of the vessel shape is carried out. This analyzing processing is allowed only when operator's confirmation is obtained (accepted) on the screen as to the center line position and the vessel surface shape.
- step S 8 and S 9 Upon the completion of the above-mentioned display of the extended vessel, it becomes possible, in the image processor 11 , to specify the range of analysis of stenosis ratio and measuring points, thus permitting analysis of the stenosis ratio in response to this specification (steps S 8 and S 9 ).
- Measuring points are specified by the image processor 11 as follows.
- FIG. 11 illustrates a typical screen for the specification of measuring points.
- This screen displays a vessel stretched image and a perpendicular sectional image, as well as buttons labelled “O” and “R”.
- buttons labelled “O” and “R” When the cursor L 1 is aligned with a position where the vessel is observed to be the thinnest on the perpendicular sectional image by moving the cursor L 1 in a straight view (see FIG. 11A ), and the “O” button is selected here, a longitudinal line is displayed at the position at the point in time of the cursor L 1 , and a label “O” is affixed to this longitudinal line.
- the configuration may be such that the positions of the measuring points can be corrected by dragging the line representing a specified point.
- the information about the extracted vessel wall is used for measuring the vessel thickness.
- an average diameter or a minimum diameter may be used, apart from a sectional area, to express the vessel thickness.
- the configuration may be such that an average diameter is displayed for a measuring point in a portion R (normal portion), and a minimum diameter is displayed for a measuring point in a portion “O” (portion of the most serious stenosis).
- the image processor 11 calculates a stenosis ratio by a calculation formula “((normal portion diameter ⁇ stenosis site diameter)/normal portion diameter) ⁇ 100(%)”, and the result value of this calculation is displayed near the longitudinal line displayed at the position of the measuring point of the portion O (portion of the most serious stenosis).
- the number of measuring points for the portion R (normal portion) is not limited to one, but two or more may be specified. When the portion R (normal portion) has only one measuring point, the diameter of the portion R is used as the normal portion diameter. On the other hand, when a plurality of measuring points are specified, the average value of diameters for the plurality of portions R may be adopted as the normal portion diameter.
- the average diameter or the minimum diameter is determined as follows.
- the vessel contour shape of a sectional image of vessel has been obtained. This contour is expressed by lines around an area RC as shown in FIG. 12 .
- the two straight lines LN 1 and LN 2 are in parallel with each other, and the distance d( ⁇ ) between them represents the vessel thickness as projected in the direction of the angle ⁇ .
- the average diameter is an average value over values d( ⁇ ), and the minimum diameter is the minimum value of d( ⁇ ).
- the operator may arbitrarily select a reference direction for each section.
- the image processor 11 may have a configuration in which, as part of the processing of analysis of stenosis described above (step S 9 ), a various factors relating to blood vessel is calculated, and displayed in the form of a graph.
- FIG. 13 illustrates a typical sectional area curve displayed together with the vessel stretched image.
- graphs regarding the vessel lumen area, the average diameter, the implemented diameter, the minimum diameter, the maximum diameter and/or the stenosis ratio can be appropriately prepared and displayed in a similar manner. The operator can intuitively understand what site of the vessel suffers from stenosis to what extent by observing these graphs. As a result, the operator can not only early discover an abnormal site of vessel, but also easily understand how the vessel thickness varies around the discovered abnormal site and over what length the abnormality is becoming more serious.
- the image processor 11 Upon the completion of display of the above-mentioned extracted vessel (step S 7 ), the image processor 11 specifies measuring points, thus permitting analysis of the vessel length corresponding to these measuring points (steps S 10 and S 11 ).
- FIG. 14 illustrates a typical analysis screen of the vessel length.
- a point P When the button “P” is pressed in the vessel stretched image by transversely moving the cursor L 1 , a point P, a measuring point, is set. A symbol “P” is provided on a curve (for example, the sectional area curve) displayed simultaneously, and the distance from the leading end of vessel range extracted at point P is displayed in mm.
- a curve for example, the sectional area curve
- the specification can be modified by moving the cursor, and then pressing again the button “P” or “D”.
- the position of the measuring points may be made correctable by dragging the line representing the specified measuring point.
- the length displayed by the analysis of such a vessel length is not a three-dimensional space-like Euclidean distance, but a length along the vessel center line.
- the vessel center line is a curve represented by a plurality of control points (typically a cubic spline curve), and can express coordinates on the curve in the form of a parameter such as x(t) by using a parameter t.
- the operator can specify two points on the vessel center line only by moving the cursor L 1 on the vessel stretched image to the right or to the left. In this case, the operator can determine these measuring points while observing a change in the vessel thickness by means of the vessel stretched image and the sectional area curve.
- the method for specifying measuring points on the vessel stretched image in this embodiment permits easy determination of what portion of the vessel the specified measuring point corresponds to, and as required, makes it possible to easily correct a once specified position of the measuring point, leading to a higher reliability of the result of length analysis.
- the image processor 11 Upon the completion of display of the above-mentioned extracted vessel (step S 7 ), the image processor 11 specifies measuring points, thus permitting analysis of the vessel bending angle in response to the specified points (steps S 12 and S 13 ).
- the vessel bending angle is calculable by:
- the first variation relates to a processing for facilitating grasping of the orientation (spatial positional relationship) executed by the image processor 11
- a measure for facilitating grasping of orientation is an orientation instructing function in the straight view (vessel stretched image). More specifically, it is the marker display.
- markers o and x are displayed on the vessel wall corresponding to the primary screen in correspondence to the vessel wall A (left) and the vessel wall B (right) on the vessel stretched image. This indicates the relationship between the right and left directions of the blood vessel.
- This display is applicable to both a case where the amount of twist is corrected and a case where the amount of twist is not corrected. If the vessel stretched image contains vessel's apparent twist, it becomes difficult to grasp the positional relationship. To solve this problem, a marker o or x is displayed on the vessel wall on the vessel stretched image. Then, a marker of the same kind is displayed at the corresponding position of the vessel wall on the primary screen. A similar marker display is made also on a perpendicular sectional image (see FIG. 15A ).
- FIG. 15B illustrates a case where markers are displayed on both sides of the vessel of a reference image on the primary screen at a position of the vessel corresponding to the cursor bar of the vessel stretched image.
- the perpendicular sectional image has two corresponding marker positions to the right and to the left of the vessel. The marker is displayed at these two points.
- FIG. 15C illustrates a case where a marker is displayed at the same position as in FIG. 15A on the perpendicular sectional image; a marker is displayed at the same position as in FIG. 15A also in the reference image on the primary screen; and furthermore, the shape of the vessel contour of the reference image of the primary screen is displayed in weight.
- the vessel stretched image in correspondence to the right-left positional relationship of two markers (o and x) on the reference image, corresponding markers are displayed to the right and to the left of the cursor bar.
- an orientation instructing function using a bent clip face in the straight-view vessel stretched image As another measure for facilitating grasping of the orientation, there is provided an orientation instructing function using a bent clip face in the straight-view vessel stretched image.
- a bent clip face corresponding to the section of the vessel stretched image is displayed on the primary screen to permit grasping of the orientation of the section of the vessel stretched image.
- the normal direction of the vessel stretched image is displayed by an arrow on the primary screen.
- volume data for clipping indicating a range to be displayed of a volume rendering image are provided. It is determined whether or not the boxel position of each volume data has a distance from the vessel center line smaller than a certain value and whether or not it is within an area existing on this side of the section in the straight view vessel stretched image; and the result of determination is reflected in the clipping volume data.
- the volume data for clipping may be stored as boxel data of which the true or false result of determination is recorded in correspondence to all the boxels of the volume, or may be stored in a information-compressed form equivalent to storing all such data.
- a line A corresponding to the cursor bar position on the vessel stretched image of the straight view is displayed on the volume rendering image, the MIP image or the flat reformatted image on the primary screen; a vector directed toward this side of the screen, which is perpendicular to the sectional plane of the vessel stretched image is determined; and an arrow directed toward this vector is displayed at a position corresponding to the vessel center line of the line A of the primary screen.
- an interlocking processing from the reference image on the primary screen to the vessel stretched image on the straight view is provided.
- the method using the vessel stretched image on the straight view and the perpendicular sectional image on the perpendicular view is a convenient display method for observing a change in the vessel thickness or the sectional shape.
- difficulty is pointed out in identifying the positional relationship between vessels of the patient and other tissues of the patient. This is because, from the images displayed on these sections alone, it is impossible to easily determine the positional relationship as to from what of the surrounding tissues the sections have been cut.
- this problem can be solved by providing simultaneously a reference image having view directions relating to positions of the sectional images in addition to the vessel stretched image and the perpendicular sectional image.
- FIG. 17 shows a case where three screens including a vessel stretched image, a perpendicular sectional image, and a reference image are displayed within a single monitor screen.
- a partial MIP image of the patient taken in a view direction is displayed.
- An MIP image is displayed in this case as an example.
- a volume-rendering image or a flat reformatted image may however be displayed.
- the view direction is changeable by a mouse or keyboard operation.
- a reference image is drawn by the image processor 11 by using a coordinate conversion matrix representing an initial view direction depending upon operator's operation or a coordinate conversion matrix representing the new modified view direction.
- a curved reformatted image which is perpendicular to the view direction vector of the reference image and has a straight line passing through the vessel center line and perpendicular to the vessel center line as the abscissa is prepared, and this image is displayed on the straight view as a vessel stretched image.
- a straight line is first determined, as shown in FIG. 18A , which is perpendicular to the vessel center line and perpendicular to the view vector for each point obtained by dividing the vessel along the vessel center line from point S (leading end point of the extracted vessel) at intervals corresponding to single pixels of the vessel stretched image, and this is used as a first axis of the vessel stretched image.
- the vessel stretched image is prepared by sampling images at equal intervals along this vector, and this image is displayed on the straight view.
- h represents the length per pixel of the perpendicular sectional image
- p(t) a point on the vessel center line (at a distance t from point S).
- the section of the vessel stretched image can be rotated by rotating a cursor bar on the perpendicular sectional image in this state.
- a cursor bar on the perpendicular sectional image in this state.
- the direction of the perpendicular sectional image can easily be determined since a relationship is always established so that the depth of the primary screen is directed substantially downward of the plane of the perpendicular view. Because a section substantially in parallel with the primary screen forms the vessel stretched image when a cursor bar is horizontal on the perpendicular sectional image, it is possible to obtain easily information about which of the sections corresponds to the vessel stretched image.
- the second variation relates to interlocking from the vessel stretched image on the straight view to the reference image on the primary screen (tangential view mode) executed by the image processor 11 .
- the technique used in the above-mentioned first variation is not always sufficient. In other words, only an appropriate positional relationship is identifiable, and this may require much time and trouble.
- a screen moving method (tangential view mode) useful in such cases is provided. Specifically, the method is executed by the image processor 11 in the following procedure.
- the image processor 11 sequentially conducts the following steps in response to this, as schematically shown in FIG. 19 .
- the reference image is drawn again on the primary screen ( FIG. 19 , steps S 120 and S 121 ).
- An axis is set as follows upon displaying the above.
- the perpendicular sectional image at a cursor bar position t 1 of the vessel stretched image is displayed.
- the vectors in the axial direction of this image are represented by e, t(t 1 ), and u(t 1 ), and the vectors of axes of the vessel stretched image are expressed by e′(t 1 ), t(t 1 ), and u′(t 1 ).
- the reference image is drawn by setting a first axis directed toward the right on the screen in the direction of e′(t 1 ), a second directed downward on the screen in the direction of t(t 1 ), and a third axis directed toward the depth of the screen in the direction of u′(t 1 ).
- Any of the MIP image, the volume-rendering image, and the flat reformatted image may be selected and displayed by operator's operation on the primary screen.
- a marker is displayed at a position corresponding to the cursor bar of the vessel stretched image on the reference image of the primary screen (step S 122 ).
- a marker is displayed at a position corresponding to the cursor bar of the vessel stretched image on the reference image of the primary screen (step S 122 ).
- the monitor screen shown in FIG. 20 is obtained.
- the perpendicular sectional image is drawn again (i.e., re-depicted) by calculating e, t(t 1 ), and u(t 1 ) in the same calculation method as in the first variation, using the view direction vector v of the reference image before the mode change.
- the reference image is drawn again using e′(t 1 ), t(t 1 ), and u′(t 1 ) as the first, second and third axes at a new position of the cursor bar CB 1 (steps S 123 and S 124 ).
- e′(t 1 ), t(t 1 ), and u′(t 1 ) are calculated again by the same calculation method as in the first variation, and the vessel stretched image is drawn again (i.e., re-depicted). And the reference image is drawn again corresponding to a vector e′(t 1 ), t(t 1 ), and u′(t 1 ) in response to the rotation of the cursor bar CB 2 (steps S 125 and S 126 ).
- the above-mentioned interlocking display is applicable to interlocking from the rotation of the perpendicular sectional image to the reference image on the primary screen.
- the first variation relates to a method for extracting a vessel center line, which specifies a passage point, executed by the image processor 11 .
- FIG. 21A illustrates a state in which, because of the presence of an obliteration and branching of vessels, there is an error in extraction of the center line between S and E.
- This method for extracting the vessel is executed by the image processor 11 in the processing procedure shown in FIG. 22 .
- the image processor 11 prepares, as described above, a volume-rendering image, an MIP image, or a flat reformatted image from three-dimensional image data of the patient, and displays the prepared image on the primary screen as a reference image.
- the image processor 11 prepares a curved reformatted image, and displays the prepared image simultaneously with the above, as a confirmation image side by side on the primary screen ( FIG. 22 , step S 200 ; see for example FIGS. 5 and 6 described above).
- the curved reformatted image may also be used as a reference image.
- the vessel stretched image may be used in place of the curved reformatted image.
- the image processor 11 accepts the specification of points S and E specifying the extraction range of vessels received from the operator via the input unit 14 (step S 201 ), and extracts and displays the vessel center lines within the ranges of points S and E on the basis of this specified point information (step S 202 ).
- the image processor 11 displays the extracted vessel center line in superposition on the MIP image, the VR (volume-rendering) image, or the flat reformatted image serving as a reference image, and on the curved reformatted image serving as a confirmation image (step S 203 ).
- the image processor 11 changes the sectional position, sectional direction, or the view direction of the reference image displayed in superposition, interactively in response to operator's operation.
- the operator determines whether or not the extracted vessel center line is appropriate from the state of display of the reference image and the confirmation image, using this interface function (step S 204 ).
- the image processor 11 may instruct the operator to manually make a correction on the screen (step S 205 and S 206 ), or retry extraction of the vessel center line by adding a passage point of the vessel center line (S 205 , S 207 to S 211 ).
- the image processor 11 When extracting the vessel center line again, the image processor 11 enters information about the passage point provided by the operator via the input unit 14 (step S 207 ), carries out processing of the sequential relationship of the new passage point with those already specified (step S 208 ), and prepares and displays lines connecting the passage points (step S 209 ). The image processor 11 determines the necessity to add or move the passage points (step S 210 ), and as required, repeats the processing of steps S 207 to 209 . If not necessary, vessel center lines are extracted again on the basis of the updated information on the passage points (step S 211 , returns the process to step S 204 , and repeats the above-mentioned processing.
- a point specified by the operator using the input unit 14 on the reference image on the primary screen is additionally entered as a passage point M 1 (step S 207 ).
- a sequential relationship S-M 1 -E is set, and two dotted lines S-M 1 and M 1 -E are displayed so as to enable the operator to confirm the sequential relationship (steps S 208 and S 209 ; see FIG. 23A ).
- the image processor 11 executes re-extraction of the vessel center line (step S 210 ).
- the image processor 11 derives all sets of two points from the set sequential relationship. In this case, they include three sets S-M 1 , M 1 -M 2 , and M 2 -E. Then, a vessel center line is extracted from each of these three sets. Upon extraction, when two lines extending from both end points are not connected, they are connected into one line by connecting the nearest points of these lines. A single vessel center line between S and E is prepared by connecting the three extracted vessel center lines, and the superposing display so far effective is changed.
- the image processor 11 updates the curved reformatted image serving as the confirmation image in response to the latest vessel center line (step S 211 ). This makes it possible to observe the change in the curved reformatted image resulting from this passage point processing substantially in a real-time manner during the addition of a new passage point and the positional connection thereof.
- the image processor 11 asks the operator whether or not the addition of the passage point and the positional correction thereof have been completed (step S 212 ).
- the process is returned to step S 207 , and if the operation is determined to have been completed, the process is returned to step S 204 .
- the operator can carry out confirmation again as to whether or not the vessel center line is properly extracted (step S 204 ).
- the above-mentioned series of operations can be repeated until the vessel center line is properly extracted, or the vessel center line is manually connected into a proper center line, or the extracting operation itself of the vessel center line is cancelled. That is, when it is determined by the operator that the vessel center line has not been properly extracted, the vessel center line can be corrected and re-extracted as described above.
- the image processor 11 allows various analyzing processes of the vessel shape (step S 213 ).
- the vessel center line can be extracted stably at a high accuracy only through simple additional specification of a few passage points by providing an automatic correction mechanism of vessel center lines in response to the addition of passage points and the positional correction thereof.
- the burden is largely alleviated as compared with the manual correction of the vessel center line.
- FIGS. 24 to 33 A second embodiment of the processor for analyzing a tubular structure of the present invention will be described with reference to FIGS. 24 to 33 .
- This embodiment provides a processor for analyzing a tubular structure which permits efficient identification of the sectional shape in the three-dimensional display of a vessel image, particularly observation of portions around a stenosis site and the position in the whole blood vessels. More specifically, the processor for analysis has a function permitting correction of the contour of an extracted area in a vessel stretched image, a straight view, and a perpendicular sectional image, a perpendicular view; a function to display in parallel a stenosis ratio curve on the vessel stretched image; a function to cut an area to be analyzed and three-dimensionally display the cut area; a jumping function of the image display position, and a parametric display function.
- the processor for analyzing a tubular structure in this embodiment has the same hardware configuration as that shown in FIG. 1 .
- a display unit 13 provides a monitor display screen.
- a GUI (Graphical User Interface) section 13 A and an image display unit 13 B are displayed on the screen. This makes it possible for the display unit 13 B to display image data stored in a video memory 11 A provided in the image processor 11 .
- the GUI section 13 A has various buttons for operating the processor for analysis arranged therein, and is operated by means of a mouse 14 A provided as a part of an input unit 14 .
- the image processor 11 has hardware components such as a CPU 111 , a memory 11 R, and a video memory 11 A.
- the CPU 111 reads out a processing program stored in advance in a memory 12 and processes three-dimensional image data on the basis of this processing program, thereby giving various functions shown in FIG. 24 to the image processor 11 .
- the image processor 11 takes charge of image processing and functionally has:
- the mouse operation input processing section 11 B performs data processing regarding operations on the monitor display screen conducted by the operator via the mouse 14 A.
- the image data storing section 11 C stores three-dimensional image data read out from the memory 12 .
- the three-dimensional image data (volume image data) manages sectional images perpendicular to the body axis direction in positional sequence along the body axis, which are managed together with information showing the human body direction in the volume image data.
- the tubular structure extracting section 11 D extracts image data of the tubular structures such as blood vessels from the volume image data by a desired area extracting method.
- the applicable area extracting methods include, for example, a technique for automatically extracting three-dimensional blood vessels and blood clot areas from X-ray CT angiographic images developed by Marko Subasic et al. (see reference “3-D Image analysis of abdominal aortic aneurysm” Medical Imaging 2001: Image Processing, Proceedings of SPIE, vol. 4322 (2001), p. 388-394).
- the extracted vessel areas are stored in the memory 11 R as tubular structure models (surface models having an apex of a sampling point on the contour).
- Other technique may be used in place of the above-mentioned extraction method.
- the center line extracting section 11 E extracts center lines in an extracted three-dimensional vessel area.
- the applicable methods for extracting center lines include, for example, the technique for automatically extracting three-dimensionally vessel center lines from an X-ray CT angiographic image, developed by Onno Wink et al. (see reference “Fast Delineation and Visualization of Vessel in 3-D Angiography Images” IEEE Transactions on Medical Imaging, vol. 19, no. 4, April 2000). Other technique may be applied in place of this center line extracting method.
- the straight volume preparing section 11 F reconstructs the volume data by piling up sectional images perpendicular to the vessel center line CL so that the vessel center line CL becomes straight as shown in FIG. 25 .
- the sectional images are piled up, on the basis of human body directional information of the image data stored in the image data storing section 11 C, so that, as the reference direction, the direction from chest to back of the human body is directed upward of the sectional images.
- the data prepared as described above is hereinafter referred to as “straight volume data”.
- the vessel stretched image preparing section 11 G prepares a sectional image including a vessel center line from straight volume data (straight view; see FIG. 25C ). Particularly, it prepares a sectional image at a position specified by the position changing section 11 I.
- the perpendicular sectional image preparing section 11 H prepares a sectional view perpendicular to the vessel center line in the straight volume data (perpendicular view; see FIG. 25C ). Particularly, it prepares a sectional view at a position specified by the sectional position changing section 11 I.
- the sectional position changing section 11 I can determine the sectional position where it generates a vessel stretched image/perpendicular sectional image, in response to operators operation. More specifically, this section has a step sectional displacement mode, and in this displacement mode, can change the sectional position at a set step value (an angle rotating around the vessel center line for the straight view; distance or a number of boxels along the vessel center line for the perpendicular view).
- the sectional position changing section 11 I has a jumping mode to a maximum position of the stenosis ratio curve calculated by the stenosis ratio calculating section 11 M.
- this section displays the maximum stenosis ratio position at the center of the straight view, and automatically set an enlargement magnifications of the display of the ranges including the maximum value toward both sides covering ranges in which the stenosis ratio if at least a certain value, as the display range of the straight view.
- the straight view is a section having the maximum value of stenosis ratio, and is set on a section passing through the minimum diameter. In this case, the sectional image at a position having the maximum value of stenosis ratio is displayed on the perpendicular sectional image, a perpendicular view.
- the center position of the straight view and the sectional position of the perpendicular view may be set using a curve of the vessel sectional area or diameter, in place of the stenosis ratio curve.
- the position of the minimum or maximum value of the curve should be adopted as the jumping position.
- the maximum value should be selected in the case of aneurysm or the like, and the minimum value, in the case of stenosis.
- the sectional position changing section 11 I has a mode in which, when setting a particular pixel value from the window specifying a specific pixel value set in the GUI section 13 A, the process jumps to a section including the area having that pixel value (for example, the calcification area or the soft plaque area).
- this section searches for a section of the straight view/perpendicular view having an area including the specified pixel value for each of the direction of rotation around the vessel center line and the direction along the vessel center line, with a stepping value set currently in the stepping displacement mode, and generates such section on the display section.
- the reference position of jumping shall be the position of center of gravity of the area having the specific pixel value.
- the priority of search is, for example, in a direction from the center to terminal of vessels, and then in the clockwise direction around the center line.
- the structure contour correcting section 11 J displays the contour of a tubular structure contour model extracted by the structure extracting section 11 D in superposition on the vessel stretched image and the perpendicular sectional image, and writes it into the video memory 11 A.
- the section changes the displayed contour in response to operator's operation.
- the tubular structure contour model has a sampling point on the contour as the apex. By dragging this apex with the mouse 14 A, the apex moves on the sectional plane in response to the operation.
- the neighboring apices in the three-dimensional space of the displaced apex also move onto approximation curves connecting the neighboring apices, thereby permitting correction of the tubular structure contour model.
- the structure contour correcting section 11 J rewrites data of the video memory 11 A so that the result of correction is reflected also in the tubular structure contour models displayed in superposition on the vessel stretched image and the perpendicular sectional image, respectively.
- the sectional area/diameter calculating section 11 L has a function to calculate the sectional area of a section perpendicular to the vessel center line, and the diameter and the radius passing through the vessel center line on the basis of the tubular structure contour model.
- the hypothetical normal structure model preparing section 11 K has a function to prepare data of a model in a hypothetical normal state of a tubular structure (hypothetical normal structure model). Specifically, as show in FIG. 32 , this preparing section 11 K approximates a graph drawn by plotting values of distance (radius) of the apex of the tubular structure contour model (sampling point on the contour) from the vessel center line by means of the regression line. Then, sampling points lower than the regression line are erased.
- this processing is repeated until the sum of relative square error between the radius and the regression line at the remaining sampling points (value of diameter ⁇ regression line at the sampling point) ⁇ 2/(sampling point diameter) ⁇ 2 becomes smaller than a certain threshold value, and the radius is determined again from the regression line. Then, a hypothetical normal tubular structure model is prepared by moving the apex position in the radial direction in response to the re-determined radius.
- the regression line may be a regression curve.
- the stenosis ratio calculating section 11 M calculates the stenosis ratio of the tubular structure on the basis of the sectional shapes of the structure contour model and the hypothetical normal structure model.
- the area Aa of the section a of the structure contour model on the perpendicular view, and the area Ab of the section b of the hypothetical normal tubular structure model on the perpendicular view are determined.
- the stenosis ratio calculating section 11 M calculates the stenosis ratio in accordance with the formula (Ab ⁇ Aa)/Ab ⁇ 100(%) using these area values.
- the value of (Db ⁇ Da)/Db ⁇ 100(%) may be calculated as a stenosis ratio by determining the minimum diameter (Da) of the section A and the diameter at a position corresponding on the section b or the average diameter (Db).
- the stenosis ratio curve preparing section 11 N prepares a stenosis ratio curve by plotting the stenosis ratio calculated by the stenosis ratio calculating section 11 M in a direction along the vessel center line.
- the stenosis ratio curve is written into the video memory 11 A so as to display the curve in correspondence to the straight view (see FIG. 31 ).
- the function of the parametric image preparing section 11 O will now be described with reference to FIG. 28 .
- the parametric image preparing section 11 O builds a wire frame model having joints obtained from the points resulting from conversion of the apices of the structure contour model in the straight volume onto the coordinate system of the original image data.
- the radius, the diameter, the sectional area, or the stenosis ratio of the structure model on the perpendicular view is allocated to each joint.
- Joints are added at the average coordinate positions over four neighboring joints until the distance between joints of the wire frame becomes smaller than a certain threshold value.
- the values (radius, diameter, sectional area, or stenosis ratio) allocated to adjacent joints are interpolated in response to the joint distance and the result is allocated to the added joints (this is referred to as the “parametric model).
- the parametric image preparing section 11 O has a configuration so as to perform three-dimensional display of the tubular structure using the parametric model prepared as described above. Upon this display, the preparing section 11 O prepares display image data so as to change the surface color in response to the allocated values to the joints.
- the data may be prepared so as to display a surface having a joint exceeding a certain threshold value in red, or the display image may be prepared, for example, in colors having continuous gradations from blue to red.
- An image prepared as described above is referred to as a parametric image.
- the function of the specific area three-dimensional preparation section 11 P will now be described with reference to FIG. 30 .
- the specific area three-dimensional preparation section 11 P has a function to perform three-dimensional display of the original volume image data corresponding to the range displayed on the straight view.
- a conventionally known arbitrary sectional image and a pseudo three-dimensional display may be combined in fusion (see FIGS. 30A and 30B ). This makes it possible to conduct general operations such as capacity setting in the three-dimensional display, image rotation, change in enlargement ratio, and panning.
- the arbitrary sectional image in this case is prepared as a section at the sectional position of the straight view (usually forming a curved surface when the vessel is bent), at the sectional position of the perpendicular view, or as a section in the tangential direction of the vessel center line. That is, when changing the sectional position of the straight view and the perpendicular view, the arbitrary sectional position is also changed.
- the sectional positions of the straight view and the perpendicular view may be set so as to be changed in conjunction.
- Setting may permit front clip display using the arbitrary section as a clip surface (see FIG. 30E ).
- the hypothetical normal structure model prepared by the hypothetical normal structure model preparing section 11 K may be displayed in fusion in response to operator's selecting operation (see FIG. 30C ).
- Setting may also permit “fly-through” display which prepares an image in response to a change in the starting point and the view direction by mouse operation (see FIG. 30D ).
- the range of area to be displayed may arbitrarily specified irrespective of the display range of the straight view.
- the volume data display preparing section 11 Q prepares an MPR image of volume image data, a projected image of MIP or the like, or a volume-rendering image, prepares image data by superposing a graphic showing the sectional position of the perpendicular view currently displayed over that image, and writes the image data into the video memory 11 A.
- the memory 11 R provided in the image processor 11 temporarily stores data to be processed by the processor 11 .
- the video memory 11 A stores image data prepared by the GUI section 13 A and the image processing section 13 B. The contents of the video memory and displayed on the monitor screen. Using the mouse 14 A, the user can instruct button operation of the GUI section 13 A and operation of the image displayed on the image display section 13 B.
- the image processor 11 processes such an image display and analyzing processing in the sequence of selection of image data (step S 41 ); extraction of a tubular structure (step S 42 ); extraction of tubular structure center line (step S 43 ); default image display (step S 44 ; including vessel extended display (straight view), perpendicular sectional display (perpendicular view), volume data display, and display of specific area three-dimensional image under the default condition); correction of a tubular structure contour model (step S 45 ); calculation of the stenosis ratio; display of stenosis ratio curve; preparation of a parametric image (step S 46 ); and then image operation (step S 47 ).
- Screen operations include the moving operation of the sectional position of the straight view and the perpendicular view; sectional jumping operation; specific area three-dimensional image operation (clipping ON/OFF); parametric display ON/OFF; parameter switching; and volume data display operation (MPR/projection/volume-rendering display switching, change in display conditions).
- the image processor 11 starts up the image selecting GUI (not shown), and displays a list of data stored in the image data storing section 11 C.
- the selected data are written from, for example, the memory unit 12 into the memory 11 R (step S 41 ).
- the image processor 11 applies a tubular structure extraction processing to the image data written in the memory 11 R by means of the structure extracting section 11 D thereof, and prepares an actual tubular structure contour model (step S 42 ).
- the image processor 11 extracts a vessel center line of the extracted tubular structure by means of the center line extracting section 11 E (step S 43 ).
- the straight volume preparing section 11 F prepares straight volume data on the basis of the vessel center line and image data.
- the vessel stretched image preparing section 11 G and the perpendicular sectional image preparing section 11 F are started up. That is, the vessel stretched image preparing section 11 G prepares a vessel stretched image, a straight view, from the straight volume data under the default sectional position and display conditions; the perpendicular sectional image preparing section 11 F prepares a perpendicular sectional image, a perpendicular view; and these image data are written into the video memory 11 A.
- the volume data display preparing section 11 Q prepares an image for volume data display of the image data under the default display conditions, and the prepared image data are written into the video memory 11 A.
- the specific area three-dimensional preparation section 11 P prepares a three-dimensional display image for the original image data corresponding to the display range of the straight view, and the prepared image data are written into the video memory 11 A.
- the monitor 13 displays the image data written into the video memory 11 A as a default image, for example, as shown in FIG. 29 .
- the image processor 11 provides the operator with a chance for manually correcting the contour of the tubular structure such as blood vessels currently displayed, via the structure contour correcting section 11 J (step S 45 ).
- the structure contour correcting section 11 J writes, by means of the function thereof, contour data of the contour model of the tubular structure extended by the structure extracting section 11 D into the video memory 11 A, and displays the contour model in superposition over the vessel stretched image and the perpendicular sectional image, respectively.
- the operator who observes the superposition-displayed contour model, if desiring to correct the model issues an instruction to correct the contour to the image processor 11 (the structure contour correcting section 11 J) via the mouse 14 A or the like.
- the contour model of the tubular structure has the sampling point on the contour as an apex.
- the apex can be moved on the section in response to dragging operation. Therefore, under the effect of the function of the structure contour correcting section 11 J, neighboring apices in the three-dimensional space of the displaced apex automatically move in conjunction to an appropriate position on an approximation line connecting the neighboring apices, and the tubular structure contour model is thus corrected.
- the result of correction is also reflected in the contour image displayed in superposition over the vessel stretched image, a straight view, and the perpendicular sectional image, a perpendicular view, through rewriting processing of the image data in the video memory 11 A.
- the sectional positions of the straight view and the perpendicular view can be displaced individually by dragging sectional position bars B 1 and B 2 , respectively (see FIG. 29 ).
- a step moving operation button B 3 By clicking a step moving operation button B 3 , the sectional position is moved by a step amount set by the sectional position changing section 11 I. Images of this sectional position and prepared by the vessel stretched image preparing section 11 G and the perpendicular sectional image preparing section 11 H, respectively, and the contour of the prepared structure contour model are superposed on the vessel stretched image and the perpendicular sectional image, respectively, on the monitor 13 through writing processing of the output image data in the video memory 11 A by the structure contour correcting section 11 J.
- the image processor 11 executes processing of stenosis ratio calculation, stenosis ratio curve display, and preparation of a parameter image (step S 46 ; see FIG. 31 ).
- the hypothetical normal structure model preparing section 11 K prepares, under the effect of functions thereof, a hypothetical normal structure model on the basis of already actually available structure contour model such as that of the blood vessel.
- the stenosis ratio calculating section 11 M calculates, under the effect of the function thereof, the stenosis ratio of the tubular structure from sectional shapes of the actual structure contour model and the hypothetical normal structure model.
- the stenosis ratio on the section of the currently displayed perpendicular view is displayed in superposition on the perpendicular view via data writing into the video memory 11 A.
- the stenosis ratio curve preparing section 11 N prepares stenosis ratio data obtained by plotting the stenosis ratios calculated by the stenosis ratio calculating section 11 M in a direction along the vessel center line. Data of the stenosis ratio curve is written into the video memory 11 A so as to display the data in correspondence to the vessel stretched image, and as shown in FIG. 31 , displayed on the monitor 13 .
- the parametric image preparing section 11 O prepares the above-mentioned parametric model by use of the function thereof, and stores the model in the memory 11 R.
- step S 47 the image processor 11 enables the operator to conduct various image operations. These operations will now be described for the individual kinds.
- sectional position bar B 2 and B 1 representing the sectional position of the straight view and the perpendicular view by dragging them on the images.
- the sectional position is changed by the sectional position changing section 11 I, and in response to this change, image data of the changed sectional positions are prepared by the vessel stretched image preparing section 11 G and the perpendicular sectional image preparing section 11 H, and written into the video memory 11 A.
- the arbitrary sectional position is changed by the specific area three-dimensional image preparing section 11 P, and image data at the sectional position thereof are prepared. These image data are also written into the video memory 11 A.
- the image data written into the video memory 11 A are read out every certain period of time and displayed on the monitor 13 .
- the volume data display preparing section 11 Q prepares data obtained by superposing a graphic showing the updated sectional position of the perpendicular view, and such image data are displayed on the monitor 13 via data rewriting processing to the video memory 11 A.
- this section operation there occurs a jumping operation of the section to the maximum position of the stenosis ratio, or a jumping operation to a section having a specific pixel value. More specifically, when clicking a “maximum stenosis ratio jump” key B 5 , or a “specific pixel value jump” key B 6 , it is possible to cause jumping at a time of the sectional position as described above. With this jumping operation at this sectional position, the image display is automatically updated in conjunction. Jumping to the next position can be caused every time the key B 5 or B 6 is clicked.
- the operator can select an arbitrary sectional position for specific three-dimensional display from the sectional position of the straight view, the sectional position of the perpendicular view, and the tangential section of the vessel center line via the GUI section 13 A.
- the specific area three-dimensional preparation section 11 P prepares an image in response to such a selection and transfers the prepared image to the video memory 11 A.
- the contents stored in the video memory 11 A are therefore displayed on the monitor 13 .
- the operator an select the hypothetical normal structure model display mode via the GUI section 13 A.
- the specific area three-dimensional preparation section 11 P prepares an image of the hypothetical normal structure model in fusion, and the image data is transferred to the video memory and displayed on the monitor 13 .
- the operator can select the fly-through display mode via the GUI section 13 A.
- the specific area three-dimensional preparation section 11 P prepares an image based on a change in the starting point and the view direction by mouse operation.
- the prepared image data is written into the video memory 11 A and displayed on the monitor 13 .
- the operator can select the front clip display mode using the GUI section 13 A.
- the specific area three-dimensional preparation section 11 P prepares a front clip image having an arbitrary section serving as a clip surface.
- the prepared image data is displayed on the monitor 13 through writing into the video memory 11 A.
- the parametric image preparing section 11 O prepares an image obtained by switching over the display of the tubular structure in the volume data display and a specific area three-dimensional display into a parametric image on the basis of the above-mentioned parametric model. This image data is transferred to the monitor 13 via the video memory 11 A and displayed.
- the operator can arbitrarily select a parameter (radius/diameter/sectional area/stenosis ratio) by means of the GUI section 13 A (see FIG. 31 ).
- the parametric image preparing section 11 O prepares and updates the image.
- the image is similarly prepared and updated (see FIG. 31 ).
- a color bar is simultaneously prepared. Data of this color bar is also transferred to the video memory 11 A together with the prepared image, and displayed.
- a threshold value setting slider bar can be operated to instruct for portions exceeding the threshold value specified with this bar to become red in color.
- the parametric image preparing section 11 O prepares image data so that the surface color changes in response to this, which is transferred to the video memory 11 A and displayed on the monitor 13 .
- the function of the volume data display preparing section 11 Q is activated, and prepares a projected image such as an MPR image or an MIP image of the volume image data, or a volume-rendering image.
- a projected image such as an MPR image or an MIP image of the volume image data, or a volume-rendering image.
- Data resulting from superposition of a graphic showing the sectional position of the currently displayed perpendicular view on the thus prepared image is prepared, and displayed on the monitor 13 via writing into the video memory 11 A.
- the operator can easily perform correction of the contour of the tubular structure area extended for quantitative analysis. He (she) can determine the image display position by comparing the stenosis ratios of tubular structures such as blood vessels. Since an area to be analyzed is cut and a three-dimensional image thereof is displaced, a higher-speed data processing is ensured.
- image display at the target position can be automatically accomplished from the stenosis ratio, sectional area in curvature of the diameter of the tubular structure.
- the tubular structure is displayed in colors depending upon stenosis ratio, diameter or sectional area.
- the three-dimensional structure of such a structure can therefore be identified more simply and reliably. Compared with the conventional art, therefore, a tubular structure can be grasped more easily in a three-dimensional manner. As a result, improvement of the diagnostic accuracy can be expected, and it is possible to reliably alleviate the burden imposed on the operator such as a physician.
- FIGS. 34 to 40 A third embodiment of the processor for analyzing a tubular structure of the present invention will now be described with reference to FIGS. 34 to 40 .
- This embodiment is intended to permit identification of the sectional shape in the three-dimensional display of a vessel image, particularly, easy and accurate identification of the three-dimensional secular change in lumps in the blood vessel to improve the accuracy determination of adaptability to surgery.
- the processor for analyzing of this embodiment is schematically based on the process comprising the steps of extracting the vessel center line and vessel areas (including blood vessel lumens and blood clot site) from present and past three-dimensional image data; specifying the measuring range; specifying branching position serving as a reference before and after the measuring range and aligning the positions; and carrying out a quantitative analysis and display of the result of analysis regarding lumps on the basis of images of the vessel areas in this state.
- the processor for analyzing a tubular structure of this embodiment has the same hardware configuration as that illustrated in the above-mentioned FIG. 1 , as in the second embodiment. Therefore, the image processor 11 reads out an operating program stored in advance in the memory unit 12 , and displays the functions shown in FIG. 34 by processing three-dimensional image data on the basis of this operating program.
- the display unit 13 provides a monitor display screen which displays the GUI section 13 A and the image display section 13 B.
- the display unit 13 B can display image data (including secular change image data) stored in the video memory 11 A provided in the image processor 11 .
- the GUI section 13 A has various buttons arranged for operating this processor for analysis, and is operated by means of a mouse 14 A provided as a part of the input unit 14 .
- the image processor 11 takes charge of image processing, and has a hardware configuration comprising a CPU 111 , a memory 11 , a video memory 11 A and the like. Through execution of prescribed processing programs of the CPU 111 , the image processor 11 functionally has a mouse operation input section 11 B, an image data storing section 11 C, an image preparing section 11 S, a vessel extraction processing section 11 T, an image data aligning section 11 U, a secular change calculating section 11 V, and a secular change image preparing section 11 W.
- the mouse operation input section 11 B takes charge of the measuring range setting processing and the GUI section button operation.
- the measuring range setting processing a measuring range is set on the basis of the position specified via the mouse 14 A on images of the two comparative tests displayed on the image display section 13 B of the monitor 13 .
- the GUI section button operation processing processes data relating to button operation of the GUI section 13 A on the basis of information instructed via the mouse 14 .
- the image preparing section 11 S prepares images for carrying out position specification for setting a measuring range.
- the memory 11 R calls image data of the two comparative tests stored in the image data storing section 11 C into the memory 11 R, and prepares an MPR image for each image data thereof.
- the data of the prepared MPR images are transferred to the video memory 11 A.
- the vessel extracting processing section 11 T has a function to extract the blood vessel area and the thrombosis area adhering to the vessel inner wall within the specified measuring range of the image data of two comparative tests by processing the image data stored in the memory 11 R.
- Such area extraction can be accomplished by the use of a technique for automatically extracting three-dimensionally the blood vessels and the thrombosis area from an X-ray CT angiographic image, developed by Marko Subasic et al. (reference “3-D Image analysis of abdominal aortic aneurysm” Medical Imaging 2001: Image Processing, Proceedings of SPIE vol. 4322 (2001), p. 388-394).
- This vessel extracting section 11 T has also a function to extract the center lines of an extracted blood vessel area (or center lines in the area including thrombosis site). Extraction of center lines can be effected by the use of a technique to automatically extracting the vessel center lines three-dimensionally from an X-ray CT angiographic image developed by Onn Wink et al. (paper “Fast Delineation and Visualization of Vessel in 3-D angiography Images” IEEE Transaction on Medical Imaging, vol. 19, no, 4, April 2000).
- the image data aligning section 11 U takes charge of positional alignment of the straight volume preparation processing.
- the straight volume preparation processing is carried out in the same manner as that described above (see FIG. 25 ). More specifically, directions of the image data of the two tests are aligned so that the direction of the human body is aligned with the test direction on the image data of the two comparative tests and the direction data of the human body in the image data, stored in the image data storing section 11 C. Sectional images perpendicular to the vessel center line are piled up so that the vessel center lines within the measuring range form a straight line. As a result, the image data are re-constructed. The data are piled up so that, for example, the direction of human body from chest to back, as a reference direction, becomes upward relative to the sectional image, and data referred to as straight volume data are thus prepared.
- the aligning processing is carried out for two straight volume data, as shown in FIGS. 35A and 35B , with the specified points of the measuring range as references. Corresponding sections are prepared through interpolation.
- the secular change calculating section 11 V has a function to calculate the length of diameter between corresponding planes perpendicular to the vessel center line among straight volume data of two comparative tests (test time 1 and test time 2 , the latter being a more past one), and determine the amount of change in diameter by the calculation of a formula “(diameter at test time 1 ) ⁇ (diameter at test time 2 )” This calculation is performed at certain intervals in the vessel center line, at every certain angle on a section perpendicular to the vessel center line (see FIG. 36C ).
- the secular change calculating section 11 V performs division of the amount of change in diameter by the time value of the two periods of the test time 1 and the test time 2 , and a speed of change in diameter is thus determined.
- the secular change calculating section 11 V has a function to determine the amount of change in sectional area through steps of, for the individual straight volume data of the two comparative tests (test time 1 and test time 2 ; the test time 2 being more past), calculating the sectional area of the plane perpendicular to the corresponding vessel center line, and calculating a formula “(sectional area in test time 1 ) ⁇ (sectional area in test time 2 )”. This calculation is performed at certain intervals along the vessel center line as in the calculation for the vessel diameter.
- the secular change calculating section 11 V performs division of the amount of change in sectional area by the time value for the test time 1 and the test time 2 , and thus determines the changing speed of sectional area.
- the secular change image preparing section 11 W constructs a wire frame model having points converted from the terminal points of vessel diameter in the straight volume data into coordinates of the original image data as joints, and allocating the amount of change in diameter and the speed of change in diameter calculated by the secular change calculating section 11 V.
- joints are added so that the distance between joints of the wire frame becomes less than a certain threshold value (for example, by adding a joint to the average coordinate position over four neighboring joints).
- a certain threshold value for example, by adding a joint to the average coordinate position over four neighboring joints.
- the secular change image preparing section 11 W conducts surface rendering on the basis of the prepared wire frame model.
- surface rendering surface colors are set in response to the amount of change in diameter and the speed of change in diameter allocated to the individual joint, and data of the image to be displayed are prepared.
- image data is prepared so that the surface of a joint exceeding a threshold value is drawn in red.
- image data may be prepared to as to draw the surface in a color having a continuous gradation from blue to red.
- the secular change image preparing section 11 W carries out similar processing also for the change in sectional area. That is, also for the amount of change in sectional area, image data are prepared in the same manner as in the amount of change in diameter by allocating the same amount of change in sectional area or the same speed of change in sectional area to joints of the wire frame model on the same section perpendicular to the vessel center line.
- the image data storing section 11 C has a function to store and manage image data. These medical image data are usually managed so that images of sections perpendicular to the body axis direction are in the sequence of body axis positions, together with data showing the human body direction in the image data. The image data is read out in the memory 11 R, and treated as three-dimensional image data. Image data are managed for each patient, and image data for the test of a particular patient are easily detectable.
- the memory 11 R has a function to read out the image data stored in the image data storing section 11 C, and temporarily retain the data. Pixel data for the image data are managed so as to permit specification with three-dimensional coordinates.
- the video memory 1 A retains the display image data prepared by the image preparing section 11 S and the secular change image preparing section 11 W so as to display images on the monitor 13 .
- the operator can perform the operation for setting a measuring range on the image displayed on the image display section 13 B, in addition to button operation of the GUI section 13 A, by operation the mouse 14 .
- the image processor 11 is in standby while determining whether or not the “measuring range specification” key of the GULI section is clicked (step S 53 ).
- the image processor 11 waits for operator s clicking of the “secular change observation” key of the GUI section 13 A, and transfers to the secular change analysis processing (step S 55 ).
- This secular change analysis is executed in the following procedure.
- the secular change calculating section 11 V of the image processor calculates an amount of change in diameter and a speed of change in diameter.
- the secular change image preparing section of the image processor 11 is activated, which prepares a secular change image, and transfers the data to the video memory 11 A.
- the image processor 11 performs processing corresponding to the observation processing of the secular change image interactively with the operator (step S 56 ).
- the surface color of surface rendering can be selected on the basis of the “threshold value” or the “gradation” by operating clicking operation to the GUI section 13 A.
- the secular change image preparing section 11 W prepares an image, and causes switching of the image displayed on the image display section 13 B of the monitor 13 .
- the secular change image preparing section 11 W prepares a color bar at the same time, and causes the image display section 13 B to display the color bar (see the image display section 13 B in FIG. 39 ).
- the secular change image preparing section 11 W reacts to this, prepares image data so that the pixel portion showing a value exceeding the threshold value is red in color, and causes switching of the display on the image display section 13 B.
- the tubular structure can be drawn with a natural contour. It is possible to more stably analyze the shape of the tubular structure at a higher accuracy. The labor required for manual editing of control points for setting the center line or the contour of a tubular structure can be largely reduced.
- the processor of the present invention can provide properly the information regarding secular change in three-dimensional structure of a local diseased site such as lumps of a tubular structure, thus facilitating comparative observation with past of the diseased site and prediction in future.
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Graphics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Apparatus For Radiation Diagnosis (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
- Ultra Sonic Daignosis Equipment (AREA)
- Processing Or Creating Images (AREA)
- Image Processing (AREA)
- Image Generation (AREA)
- Image Analysis (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JPP2003-79117 | 2003-03-20 | ||
JP2003079117A JP4421203B2 (ja) | 2003-03-20 | 2003-03-20 | 管腔状構造体の解析処理装置 |
Publications (2)
Publication Number | Publication Date |
---|---|
US20040249270A1 US20040249270A1 (en) | 2004-12-09 |
US7369691B2 true US7369691B2 (en) | 2008-05-06 |
Family
ID=33293330
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US10/803,930 Expired - Fee Related US7369691B2 (en) | 2003-03-20 | 2004-03-19 | Processor for analyzing tubular structure such as blood vessels |
Country Status (3)
Country | Link |
---|---|
US (1) | US7369691B2 (zh) |
JP (1) | JP4421203B2 (zh) |
CN (2) | CN100343857C (zh) |
Cited By (76)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20060043264A1 (en) * | 2004-09-02 | 2006-03-02 | Casio Computer Co., Ltd. | Imaging apparatus, image processing method for imaging apparatus, recording medium and carrier wave signal |
US20070014461A1 (en) * | 2005-05-20 | 2007-01-18 | Imaging Sciences International, Inc. | Location of curved structure |
US20070073147A1 (en) * | 2005-09-28 | 2007-03-29 | Siemens Medical Solutions Usa, Inc. | Method and apparatus for displaying a measurement associated with an anatomical feature |
US20070293755A1 (en) * | 2004-09-22 | 2007-12-20 | Takashi Shirahata | Medical Image Display Device, Method, and Program |
US20080025587A1 (en) * | 2006-07-17 | 2008-01-31 | Christian Asbeck | Method and apparatus for determining the spatial profile of a vessel axis in volume data records for medical imaging |
US20080079722A1 (en) * | 2006-09-25 | 2008-04-03 | Siemens Corporate Research, Inc. | System and method for view-dependent cutout geometry for importance-driven volume rendering |
US20080119734A1 (en) * | 2006-11-22 | 2008-05-22 | Celine Pruvot | Method, system, and computer product for automatically extracting and tracking cardiac calcifications and determining a tracking centerline |
US20080154137A1 (en) * | 2006-11-22 | 2008-06-26 | Celine Pruvot | Method, system, and computer product for separating coronary lumen, coronary vessel wall and calcified plaque in an intravascular ultrasound view |
US20080205728A1 (en) * | 2005-03-09 | 2008-08-28 | Koninklijke Philips Electronics, N.V. | Apparatus and Method for Providing 2D Representation of 3D Image Data Representing an Anatomical Lumen Tree Structure |
US20080253630A1 (en) * | 2007-04-12 | 2008-10-16 | Fujifilm Corporation | Image display method, apparatus, and program |
US20090005693A1 (en) * | 2004-12-22 | 2009-01-01 | Biotree Systems, Inc. | Medical Imaging Methods and Apparatus for Diagnosis and Monitoring of Diseases and Uses Therefor |
US20090016483A1 (en) * | 2007-07-10 | 2009-01-15 | Kabushiki Kaisha Toshiba | X-ray apparatus, image processing display apparatus and computer program product |
US20090118615A1 (en) * | 2005-07-20 | 2009-05-07 | Matsushita Electric Industrial Co., Ltd. | Ultrasonic diagnostic apparatus |
US20090310847A1 (en) * | 2008-03-25 | 2009-12-17 | Takeo Matsuzaki | Medical image processing apparatus and x-ray diagnosis apparatus |
US20100002839A1 (en) * | 2008-07-04 | 2010-01-07 | Kabushiki Kaisha Toshiba | X-ray imaging apparatus that displays analysis image with taken image, x-ray imaging method, and image processing apparatus |
US20100092053A1 (en) * | 2008-10-10 | 2010-04-15 | Kabushiki Kaisha Toshiba | Medical image processor and medical image processing method |
US20100128963A1 (en) * | 2008-11-21 | 2010-05-27 | Kabushiki Kaisha Toshiba | Image processing apparatus and image processing method |
US20100160773A1 (en) * | 2007-03-08 | 2010-06-24 | Sync-Rx, Ltd. | Automatic quantitative vessel analysis at the location of an automatically-detected tool |
US20100195879A1 (en) * | 2009-01-30 | 2010-08-05 | Bernhardt Dominik | Method for actuating an image output device, method for determining tangential slice planes, actuation module and slice plane determination unit |
US20100215228A1 (en) * | 2007-06-11 | 2010-08-26 | Hitachi Medical Corporation | Medical image displaying apparatus, medical image displaying method, and medical image displaying program |
US20110119619A1 (en) * | 2009-11-19 | 2011-05-19 | Microsoft Corporation | Integrated viewfinder and digital media |
US20110135175A1 (en) * | 2009-11-26 | 2011-06-09 | Algotec Systems Ltd. | User interface for selecting paths in an image |
US20110170758A1 (en) * | 2010-01-12 | 2011-07-14 | Fujifilm Corporation | Tomographic image generating apparatus, tomographic image generating method, and program for generating tomographic images |
US20110235882A1 (en) * | 2006-09-29 | 2011-09-29 | Koninklijke Philips Electronics N.V. | Methods, system and computer program product for detecting a protrusion |
CN102214369A (zh) * | 2010-04-07 | 2011-10-12 | 英特尔公司 | 移位参数曲面的分层包围 |
US20120026162A1 (en) * | 2010-07-28 | 2012-02-02 | Fujifilm Corporation | Diagnosis assisting apparatus, diagnosis assisting program, and diagnosis assisting method |
US8157742B2 (en) | 2010-08-12 | 2012-04-17 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US8200466B2 (en) | 2008-07-21 | 2012-06-12 | The Board Of Trustees Of The Leland Stanford Junior University | Method for tuning patient-specific cardiovascular simulations |
EP2484285A1 (en) * | 2009-09-30 | 2012-08-08 | FUJIFILM Corporation | Diagnosis assisting system, diagnosis assisting program, and diagnosis assisting method |
US8249815B2 (en) | 2010-08-12 | 2012-08-21 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US20130051640A1 (en) * | 2011-07-25 | 2013-02-28 | Siemens Corporation | Method for vascular flow pattern analysis |
US20130064435A1 (en) * | 2011-09-09 | 2013-03-14 | Calgary Scientific Inc. | Determining contours of a vessel using an active contouring model |
US20130064440A1 (en) * | 2010-04-16 | 2013-03-14 | Koninklijke Philips Electronics N.V. | Image data reformatting |
US20130216119A1 (en) * | 2012-02-17 | 2013-08-22 | Siemens Medical Solutions Usa, Inc. | System for Suppressing Vascular Structure in Medical Images |
US8548778B1 (en) | 2012-05-14 | 2013-10-01 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US8675113B2 (en) | 2012-02-24 | 2014-03-18 | Research In Motion Limited | User interface for a digital camera |
US8700130B2 (en) | 2007-03-08 | 2014-04-15 | Sync-Rx, Ltd. | Stepwise advancement of a medical tool |
US8855744B2 (en) | 2008-11-18 | 2014-10-07 | Sync-Rx, Ltd. | Displaying a device within an endoluminal image stack |
US20150082153A1 (en) * | 2013-09-17 | 2015-03-19 | Samsung Electronics Co., Ltd. | Method for processing data and electronic device thereof |
US9095313B2 (en) | 2008-11-18 | 2015-08-04 | Sync-Rx, Ltd. | Accounting for non-uniform longitudinal motion during movement of an endoluminal imaging probe |
US9101286B2 (en) | 2008-11-18 | 2015-08-11 | Sync-Rx, Ltd. | Apparatus and methods for determining a dimension of a portion of a stack of endoluminal data points |
US9117141B2 (en) | 2011-10-14 | 2015-08-25 | Siemens Medical Solutions Usa, Inc. | Method and apparatus for identifying regions of interest in medical imaging data |
US9144394B2 (en) | 2008-11-18 | 2015-09-29 | Sync-Rx, Ltd. | Apparatus and methods for determining a plurality of local calibration factors for an image |
US9305334B2 (en) | 2007-03-08 | 2016-04-05 | Sync-Rx, Ltd. | Luminal background cleaning |
US20160140712A1 (en) * | 2013-05-13 | 2016-05-19 | Kabushiki Kaisha Toshiba | Medical image analyzer |
US9357980B2 (en) | 2012-01-10 | 2016-06-07 | Konica Minolta, Inc. | Ultrasound diagnostic apparatus and method for identifying blood vessel |
US9375164B2 (en) | 2007-03-08 | 2016-06-28 | Sync-Rx, Ltd. | Co-use of endoluminal data and extraluminal imaging |
US9390497B2 (en) | 2012-03-09 | 2016-07-12 | Fujifilm Corporation | Medical image processing apparatus, method and program |
US9443303B2 (en) | 2011-09-09 | 2016-09-13 | Calgary Scientific Inc. | Image display of a centerline of tubular structure |
US9443317B2 (en) | 2011-09-09 | 2016-09-13 | Calgary Scientific Inc. | Image display of a centerline of tubular structure |
US9445777B2 (en) | 2010-03-31 | 2016-09-20 | Fujifilm Corporation | Projection image generation apparatus, program and method |
US9558589B2 (en) | 2012-09-12 | 2017-01-31 | Fujifilm Corporation | Medical image display apparatus, method, and program |
US20170032523A1 (en) * | 2014-04-10 | 2017-02-02 | Sync-Rx, Ltd | Image Analysis in the Presence of a Medical Device |
US20170071554A1 (en) * | 2015-09-16 | 2017-03-16 | Fujifilm Corporation | Tomographic image generation device, method and recording medium |
US9629571B2 (en) | 2007-03-08 | 2017-04-25 | Sync-Rx, Ltd. | Co-use of endoluminal data and extraluminal imaging |
US9855384B2 (en) | 2007-03-08 | 2018-01-02 | Sync-Rx, Ltd. | Automatic enhancement of an image stream of a moving organ and displaying as a movie |
US9865079B2 (en) | 2010-03-31 | 2018-01-09 | Fujifilm Corporation | Virtual endoscopic image generated using an opacity curve |
US9888969B2 (en) | 2007-03-08 | 2018-02-13 | Sync-Rx Ltd. | Automatic quantitative vessel analysis |
US9974509B2 (en) | 2008-11-18 | 2018-05-22 | Sync-Rx Ltd. | Image super enhancement |
US10354050B2 (en) | 2009-03-17 | 2019-07-16 | The Board Of Trustees Of Leland Stanford Junior University | Image processing method for determining patient-specific cardiovascular information |
US10362962B2 (en) | 2008-11-18 | 2019-07-30 | Synx-Rx, Ltd. | Accounting for skipped imaging locations during movement of an endoluminal imaging probe |
US10699407B2 (en) * | 2018-04-11 | 2020-06-30 | Pie Medical Imaging B.V. | Method and system for assessing vessel obstruction based on machine learning |
US10716528B2 (en) | 2007-03-08 | 2020-07-21 | Sync-Rx, Ltd. | Automatic display of previously-acquired endoluminal images |
US10748289B2 (en) | 2012-06-26 | 2020-08-18 | Sync-Rx, Ltd | Coregistration of endoluminal data points with values of a luminal-flow-related index |
US11004198B2 (en) | 2017-03-24 | 2021-05-11 | Pie Medical Imaging B.V. | Method and system for assessing vessel obstruction based on machine learning |
US11064903B2 (en) | 2008-11-18 | 2021-07-20 | Sync-Rx, Ltd | Apparatus and methods for mapping a sequence of images to a roadmap image |
US11064964B2 (en) | 2007-03-08 | 2021-07-20 | Sync-Rx, Ltd | Determining a characteristic of a lumen by measuring velocity of a contrast agent |
US11081237B2 (en) | 2012-10-24 | 2021-08-03 | Cathworks Ltd. | Diagnostically useful results in real time |
US11076770B2 (en) | 2016-05-16 | 2021-08-03 | Cathworks Ltd. | System for vascular assessment |
US11138733B2 (en) | 2013-10-24 | 2021-10-05 | Cathworks Ltd. | Vascular characteristic determination with correspondence modeling of a vascular tree |
US11160524B2 (en) | 2016-05-16 | 2021-11-02 | Cathworks Ltd. | Vascular path editing using energy function minimization |
US11197651B2 (en) | 2007-03-08 | 2021-12-14 | Sync-Rx, Ltd. | Identification and presentation of device-to-vessel relative motion |
US11278208B2 (en) | 2012-10-24 | 2022-03-22 | Cathworks Ltd. | Automated measurement system and method for coronary artery disease scoring |
US11406337B2 (en) | 2012-10-24 | 2022-08-09 | Cathworks Ltd. | Calculating a fractional flow reserve |
EP4064181A4 (en) * | 2019-11-19 | 2023-11-29 | Suzhou Rainmed Medical Technology Co., Ltd. | METHOD AND APPARATUS FOR ACQUIRING CONTOUR LINES OF A BLOOD VESSEL AS A FUNCTION OF A CENTRAL LINE OF A BLOOD VESSEL |
US12039685B2 (en) | 2019-09-23 | 2024-07-16 | Cathworks Ltd. | Methods, apparatus, and system for synchronization between a three-dimensional vascular model and an imaging device |
Families Citing this family (195)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE10233668A1 (de) * | 2002-07-24 | 2004-02-19 | Siemens Ag | Bearbeitungsverfahren für einen Volumendatensatz |
JP2005198708A (ja) * | 2004-01-13 | 2005-07-28 | Toshiba Corp | 血管狭窄率解析装置及び血管狭窄率解析方法 |
US8355775B2 (en) * | 2004-06-03 | 2013-01-15 | Hitachi Medical Corporation | Image diagnosing support method and image diagnosing support apparatus |
DE102004028123B4 (de) * | 2004-06-09 | 2008-06-26 | Siemens Ag | Computertomograph mit einer Messanordung und einem Bildrechner zur Erzeugung eines dreidimensionalen Bilddatensatzes eines Körperteils eines Patienten |
US8021300B2 (en) * | 2004-06-16 | 2011-09-20 | Siemens Medical Solutions Usa, Inc. | Three-dimensional fly-through systems and methods using ultrasound data |
JP4974887B2 (ja) * | 2004-06-23 | 2012-07-11 | コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ | 3d管状オブジェクトのパラメータに関する情報を表示するための画像処理システム |
DE102004043676B4 (de) * | 2004-09-09 | 2014-01-09 | Siemens Aktiengesellschaft | Verfahren zur Visualisierung von Plaqueablagerungen aus 3D-Bilddatensätzen von Gefäßstrukturen |
EP1643453B1 (en) | 2004-09-30 | 2017-04-05 | Toshiba Medical Systems Corporation | Image processing apparatus and method for curved multi-planar reformatting |
US7532748B2 (en) * | 2004-11-24 | 2009-05-12 | General Electric Company | Methods and apparatus for selecting and/or labeling vessel branches |
JP4891541B2 (ja) * | 2004-12-17 | 2012-03-07 | 株式会社東芝 | 血管狭窄率解析システム |
JP4703193B2 (ja) * | 2005-01-14 | 2011-06-15 | 株式会社東芝 | 画像処理装置 |
JP2006246941A (ja) * | 2005-03-08 | 2006-09-21 | Toshiba Corp | 画像処理装置及び管走行トラッキング方法 |
JP4864548B2 (ja) * | 2005-05-31 | 2012-02-01 | 株式会社東芝 | 医療用レポート作成システム、当該システムを内蔵する超音波診断装置、医療用レポート作成プログラム |
JP2006346022A (ja) * | 2005-06-14 | 2006-12-28 | Ziosoft Inc | 画像表示方法及び画像表示プログラム |
EP1903943A1 (en) * | 2005-06-21 | 2008-04-02 | Koninklijke Philips Electronics N.V. | Method and device for imaging a blood vessel |
WO2006136971A2 (en) * | 2005-06-22 | 2006-12-28 | Koninklijke Philips Electronics N.V. | Method to visualize cutplanes for curved elongated structures |
JP2008543511A (ja) * | 2005-06-24 | 2008-12-04 | ヴォルケイノウ・コーポレーション | 脈管の画像作製方法 |
JP4672465B2 (ja) * | 2005-07-01 | 2011-04-20 | 株式会社日立メディコ | 医用画像診断支援装置及び画像処理プログラム |
JP4709600B2 (ja) * | 2005-07-15 | 2011-06-22 | 株式会社東芝 | X線診断装置、撮影角度最適化支援装置及びプログラム |
JP4786246B2 (ja) * | 2005-08-03 | 2011-10-05 | 株式会社東芝 | 画像処理装置及び画像処理システム |
JP2007044121A (ja) * | 2005-08-08 | 2007-02-22 | Hitachi Medical Corp | 医用画像表示方法及び装置 |
JP4901159B2 (ja) * | 2005-08-31 | 2012-03-21 | 株式会社東芝 | X線ct装置及びx線撮影方法 |
JP4327139B2 (ja) | 2005-09-05 | 2009-09-09 | ザイオソフト株式会社 | 画像処理方法および画像処理プログラム |
US7970187B2 (en) * | 2005-09-06 | 2011-06-28 | Pie Medical Imaging B.V. | Method, apparatus and computer program for contour detection of vessels using x-ray densitometry |
EP1938271A2 (en) * | 2005-10-21 | 2008-07-02 | The General Hospital Corporation | Methods and apparatus for segmentation and reconstruction for endovascular and endoluminal anatomical structures |
JP4384628B2 (ja) * | 2005-10-24 | 2009-12-16 | バイオビジック ジャパン株式会社 | 器官の状態変化を評価する装置およびプログラム |
KR100859434B1 (ko) * | 2005-11-01 | 2008-09-23 | 주식회사 메디슨 | 다중 단면영상을 이용한 컨투어 편집 기능을 제공하는 영상처리 시스템 및 방법 |
US20070109299A1 (en) * | 2005-11-15 | 2007-05-17 | Vital Images, Inc. | Surface-based characteristic path generation |
US7565000B2 (en) * | 2005-11-23 | 2009-07-21 | General Electric Company | Method and apparatus for semi-automatic segmentation technique for low-contrast tubular shaped objects |
JP4736755B2 (ja) * | 2005-11-30 | 2011-07-27 | コニカミノルタエムジー株式会社 | モデリング装置、領域抽出装置、モデリング方法及びプログラム |
JP4901212B2 (ja) * | 2005-12-28 | 2012-03-21 | 株式会社東芝 | 医用画像処理装置 |
JP4285486B2 (ja) * | 2006-01-31 | 2009-06-24 | 住友電気工業株式会社 | ケーブルの形状状態測定方法、及びこれに用いるケーブルの形状状態測定システム、ケーブルの形状状態測定プログラム、ケーブル状態評価方法 |
JP4843357B2 (ja) * | 2006-04-19 | 2011-12-21 | 株式会社東芝 | 画像処理装置 |
JP2007293550A (ja) * | 2006-04-24 | 2007-11-08 | Konica Minolta Sensing Inc | ポリゴンメッシュ編集方法、装置、システム及びプログラム |
WO2007129493A1 (ja) * | 2006-05-02 | 2007-11-15 | National University Corporation Nagoya University | 医療画像観察支援装置 |
GB2438668B (en) * | 2006-06-02 | 2008-07-30 | Siemens Molecular Imaging Ltd | Deformation of mask-based images |
JP2008000270A (ja) * | 2006-06-21 | 2008-01-10 | Aze Ltd | 生体組織の識別画像作成方法、装置およびプログラム |
KR100948047B1 (ko) * | 2006-06-29 | 2010-03-19 | 주식회사 메디슨 | 초음파 영상을 형성하는 초음파 시스템 및 방법 |
US8676300B2 (en) | 2006-09-18 | 2014-03-18 | Mediguide Ltd. | Method and system for navigating through an occluded tubular organ |
DE102006049309B4 (de) * | 2006-10-19 | 2008-07-24 | Tomtec Imaging Systems Gmbh | Verfahren, Vorrichtung und Computerprogrammprodukt zum Auswerten von medizinischen Bilddatensätzen |
US8135185B2 (en) * | 2006-10-20 | 2012-03-13 | Stereotaxis, Inc. | Location and display of occluded portions of vessels on 3-D angiographic images |
US7940974B2 (en) * | 2006-11-21 | 2011-05-10 | General Electric Company | Method and system for adjusting 3D CT vessel segmentation |
US8244015B2 (en) * | 2006-11-22 | 2012-08-14 | General Electric Company | Methods and apparatus for detecting aneurysm in vasculatures |
US8160395B2 (en) * | 2006-11-22 | 2012-04-17 | General Electric Company | Method and apparatus for synchronizing corresponding landmarks among a plurality of images |
US7957574B2 (en) * | 2006-11-22 | 2011-06-07 | General Electric Company | Methods and apparatus for generating a risk metric for soft plaque in vessels |
US8126238B2 (en) * | 2006-11-22 | 2012-02-28 | General Electric Company | Method and system for automatically identifying and displaying vessel plaque views |
FR2908976B1 (fr) * | 2006-11-24 | 2009-02-20 | Gen Electric | Procede de mesures de dimensions d'un vaisseau. |
JP5139441B2 (ja) * | 2006-11-30 | 2013-02-06 | コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ | 血管構造の可視化 |
JP5072343B2 (ja) * | 2006-12-19 | 2012-11-14 | ジーイー・メディカル・システムズ・グローバル・テクノロジー・カンパニー・エルエルシー | 磁気共鳴イメージング装置,磁気共鳴イメージング方法,拡散テンソルカラーマップ画像生成装置,拡散テンソルカラーマップ画像生成方法 |
JP5305609B2 (ja) * | 2007-04-04 | 2013-10-02 | 株式会社東芝 | X線撮影装置および透視ロードマップ画像作成プログラム |
US20080281182A1 (en) * | 2007-05-07 | 2008-11-13 | General Electric Company | Method and apparatus for improving and/or validating 3D segmentations |
JP5047686B2 (ja) * | 2007-05-08 | 2012-10-10 | 株式会社日立メディコ | 血管画像表示方法と装置 |
JP2010528750A (ja) * | 2007-06-07 | 2010-08-26 | コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ | 管状構造の検査 |
JP5319180B2 (ja) * | 2007-07-10 | 2013-10-16 | 株式会社東芝 | X線撮影装置、画像処理装置および画像処理プログラム |
JP5159195B2 (ja) * | 2007-07-12 | 2013-03-06 | 株式会社東芝 | 医用画像処理装置 |
JP2010534500A (ja) * | 2007-07-27 | 2010-11-11 | コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ | 画像位置合わせに対するインタラクティブアトラス |
EP2188782B1 (en) * | 2007-08-03 | 2018-11-07 | Koninklijke Philips N.V. | Coupling the viewing direction of a blood vessel's cpr view with the viewing angle on this 3d tubular structure's rendered voxel volume and/or with the c-arm geometry of a 3d rotational angiography device's c-arm system |
RU2491637C2 (ru) * | 2007-09-17 | 2013-08-27 | Конинклейке Филипс Электроникс Н.В. | Калибромер для измерения объектов изображения |
JP5283877B2 (ja) * | 2007-09-21 | 2013-09-04 | 株式会社東芝 | 超音波診断装置 |
US7978191B2 (en) * | 2007-09-24 | 2011-07-12 | Dolphin Imaging Systems, Llc | System and method for locating anatomies of interest in a 3D volume |
US8934604B2 (en) * | 2007-09-28 | 2015-01-13 | Kabushiki Kaisha Toshiba | Image display apparatus and X-ray diagnostic apparatus |
EP2238571B1 (en) * | 2007-12-04 | 2013-04-17 | GE Healthcare Limited | System for image processing using principal component analysis |
JP2011115187A (ja) * | 2008-03-26 | 2011-06-16 | Konica Minolta Medical & Graphic Inc | 画像計測装置、医用画像システム及びプログラム |
JP4746068B2 (ja) * | 2008-03-28 | 2011-08-10 | 一史 浦澤 | 画像解析装置及び画像解析方法 |
JP5181124B2 (ja) * | 2008-03-31 | 2013-04-10 | サイバネットシステム株式会社 | 動脈瘤計測方法、及びその装置並びにコンピュータプログラム |
JP4376944B2 (ja) * | 2008-04-03 | 2009-12-02 | 富士フイルム株式会社 | 中間画像生成方法および装置ならびにプログラム |
JP2008200524A (ja) * | 2008-05-12 | 2008-09-04 | Ziosoft Inc | 画像処理方法 |
JP4671204B2 (ja) * | 2008-07-09 | 2011-04-13 | ザイオソフト株式会社 | 医用画像表示制御装置及び医用画像表示制御プログラム |
JP4541434B2 (ja) * | 2008-07-14 | 2010-09-08 | ザイオソフト株式会社 | 画像処理装置及び画像処理プログラム |
US8165425B2 (en) * | 2008-07-24 | 2012-04-24 | Siemens Medical Solutions Usa, Inc. | Interactive manual deformable registration of images |
EP2317924A1 (en) * | 2008-08-11 | 2011-05-11 | Koninklijke Philips Electronics N.V. | Determining foreshortening optimal view maps taking into account the shape of the vessel cross-section in cardiovascular x-ray systems |
US9318026B2 (en) | 2008-08-21 | 2016-04-19 | Lincoln Global, Inc. | Systems and methods providing an enhanced user experience in a real-time simulated virtual reality welding environment |
JP5231901B2 (ja) * | 2008-08-29 | 2013-07-10 | 株式会社東芝 | 画像処理装置 |
US8582844B2 (en) | 2008-11-13 | 2013-11-12 | Hitachi Medical Corporation | Medical image processing device and method |
WO2010055817A1 (ja) * | 2008-11-13 | 2010-05-20 | 株式会社 日立メディコ | 画像処理装置及び画像処理方法 |
JP2012510317A (ja) * | 2008-11-28 | 2012-05-10 | フジフイルム メディカル システムズ ユーエスエイ インコーポレイテッド | 脊椎のラベル付けの伝搬のためのシステムおよび方法 |
JP2010207531A (ja) * | 2009-03-12 | 2010-09-24 | Toshiba Corp | Mri装置及びデータ処理装置 |
JP5388647B2 (ja) * | 2009-03-23 | 2014-01-15 | 株式会社東芝 | 医用画像処理装置及び方法、プログラム |
JP5491914B2 (ja) * | 2009-04-28 | 2014-05-14 | 株式会社東芝 | 画像表示装置およびx線診断装置 |
JP5395538B2 (ja) * | 2009-06-30 | 2014-01-22 | 株式会社東芝 | 超音波診断装置及び画像データ表示用制御プログラム |
US9098927B2 (en) | 2009-08-21 | 2015-08-04 | Kabushiki Kaisha Toshiba | Image processing apparatus for diagnostic imaging and method thereof |
CN101991420B (zh) * | 2009-08-27 | 2013-01-16 | 上海西门子医疗器械有限公司 | 一种疑似血管狭窄区域的定位方法和*** |
EP3363350B1 (en) * | 2009-09-23 | 2019-12-11 | Lightlab Imaging, Inc. | Lumen morphology and vascular resistance measurements data collection systems, apparatus and methods |
US20180344174A9 (en) * | 2009-09-23 | 2018-12-06 | Lightlab Imaging, Inc. | Lumen Morphology and Vascular Resistance Measurements Data Collection Systems, Apparatus and Methods |
JP5380231B2 (ja) | 2009-09-30 | 2014-01-08 | 富士フイルム株式会社 | 医用画像表示装置および方法ならびにプログラム |
JP5680092B2 (ja) * | 2009-10-06 | 2015-03-04 | コーニンクレッカ フィリップス エヌ ヴェ | X線画像撮影装置の位置付け方法 |
WO2011062108A1 (ja) * | 2009-11-19 | 2011-05-26 | 株式会社 日立メディコ | 画像処理装置及び画像処理方法 |
JP5597399B2 (ja) * | 2010-01-08 | 2014-10-01 | 株式会社東芝 | 医用画像診断装置 |
JP5618230B2 (ja) * | 2010-01-25 | 2014-11-05 | 学校法人日本大学 | 画像生成装置、画像生成方法およびプログラム |
JP5631629B2 (ja) * | 2010-05-17 | 2014-11-26 | 株式会社東芝 | 超音波画像処理装置及び超音波診断装置 |
JP5839822B2 (ja) * | 2010-05-17 | 2016-01-06 | 株式会社東芝 | 画像処理装置及びx線ct装置 |
JP5660432B2 (ja) * | 2010-06-30 | 2015-01-28 | 独立行政法人理化学研究所 | 領域データ編集装置、領域データ編集方法、プログラム、及び、記録媒体 |
JP5631649B2 (ja) * | 2010-07-13 | 2014-11-26 | オリンパス株式会社 | 画像情報表示方法 |
US10426430B2 (en) * | 2010-08-26 | 2019-10-01 | Koninklijke Philips N.V. | Automated three dimensional aortic root measurement and modeling |
JP5562775B2 (ja) * | 2010-09-15 | 2014-07-30 | 株式会社東芝 | 医用画像表示システム |
JP5844093B2 (ja) * | 2010-09-15 | 2016-01-13 | 株式会社東芝 | 医用画像処理装置及び医用画像処理方法 |
US8798227B2 (en) * | 2010-10-15 | 2014-08-05 | Kabushiki Kaisha Toshiba | Medical image processing apparatus and X-ray computed tomography apparatus |
JP5984237B2 (ja) * | 2010-10-15 | 2016-09-06 | 東芝メディカルシステムズ株式会社 | 医用画像処理装置及びx線コンピュータ断層撮影装置 |
JP5309109B2 (ja) * | 2010-10-18 | 2013-10-09 | 富士フイルム株式会社 | 医用画像処理装置および方法、並びにプログラム |
JP2012170536A (ja) * | 2011-02-18 | 2012-09-10 | Toshiba Corp | 超音波診断装置、画像処理装置及び画像処理プログラム |
JP5971682B2 (ja) * | 2011-03-02 | 2016-08-17 | 東芝メディカルシステムズ株式会社 | 磁気共鳴イメージング装置 |
US10186056B2 (en) * | 2011-03-21 | 2019-01-22 | General Electric Company | System and method for estimating vascular flow using CT imaging |
BR112014003281A2 (pt) * | 2011-08-16 | 2017-04-18 | Koninklijke Philips Nv | sistema, método e estação de trabalho |
JP5325951B2 (ja) * | 2011-08-17 | 2013-10-23 | 日立アロカメディカル株式会社 | 超音波データ処理装置 |
JP5841771B2 (ja) * | 2011-08-17 | 2016-01-13 | 日立アロカメディカル株式会社 | 超音波データ処理装置 |
JP5863330B2 (ja) * | 2011-08-22 | 2016-02-16 | 国立大学法人旭川医科大学 | 画像処理装置、画像処理方法、およびプログラム |
JP5216899B2 (ja) * | 2011-08-23 | 2013-06-19 | 株式会社東芝 | 画像表示装置及び画像表示方法 |
CA2850476A1 (en) * | 2011-08-26 | 2013-03-07 | EBM Corporation | Bloodstream simulation system for simulating blood vessel treatment effect, method therefor, and computer software program |
CN103930926B (zh) * | 2011-09-13 | 2017-06-13 | 皇家飞利浦有限公司 | 具有孔口可视化的脉管轮廓描绘 |
CN103813752B (zh) * | 2012-01-27 | 2017-11-10 | 东芝医疗***株式会社 | 医用图像处理装置 |
JP5215483B1 (ja) * | 2012-02-24 | 2013-06-19 | 株式会社東芝 | 医用画像処理装置 |
DE102012203122B4 (de) * | 2012-02-29 | 2023-08-03 | Siemens Healthcare Gmbh | Verfahren und System zur Ermittlung eines Begrenzungsflächennetzes |
JP5931508B2 (ja) | 2012-03-02 | 2016-06-08 | 株式会社東芝 | 医用画像処理装置 |
JP5814838B2 (ja) * | 2012-03-14 | 2015-11-17 | 富士フイルム株式会社 | 画像生成装置、方法及びプログラム |
US8958618B2 (en) * | 2012-06-28 | 2015-02-17 | Kabushiki Kaisha Toshiba | Method and system for identification of calcification in imaged blood vessels |
CN103505288B (zh) * | 2012-06-29 | 2017-11-17 | 通用电气公司 | 超声成像方法和超声成像设备 |
CN104412296B (zh) * | 2012-06-29 | 2017-12-01 | 株式会社岛津制作所 | 图像处理装置 |
US9020232B2 (en) | 2012-07-24 | 2015-04-28 | Kabushiki Kaisha Toshiba | Per vessel, vessel tree modelling with shared contours |
WO2014022804A1 (en) | 2012-08-03 | 2014-02-06 | Volcano Corporation | Devices, systems, and methods for assessing a vessel |
US9727968B2 (en) * | 2012-08-13 | 2017-08-08 | Koninklijke Philips N.V. | Tubular structure tracking |
WO2014034294A1 (ja) * | 2012-08-28 | 2014-03-06 | 株式会社日立メディコ | 画像表示装置及び医用画像撮像装置 |
JP6169927B2 (ja) * | 2012-08-31 | 2017-07-26 | 東芝メディカルシステムズ株式会社 | 医用レポート作成装置及び医用画像診断装置 |
JP5934071B2 (ja) * | 2012-09-27 | 2016-06-15 | 富士フイルム株式会社 | 管状構造の最短経路探索装置および方法並びにプログラム |
US10568586B2 (en) | 2012-10-05 | 2020-02-25 | Volcano Corporation | Systems for indicating parameters in an imaging data set and methods of use |
JP6062215B2 (ja) * | 2012-11-06 | 2017-01-18 | 東芝メディカルシステムズ株式会社 | 医用画像処理装置 |
JP6129525B2 (ja) * | 2012-11-20 | 2017-05-17 | 東芝メディカルシステムズ株式会社 | 画像処理装置、及びx線診断装置 |
US9091628B2 (en) | 2012-12-21 | 2015-07-28 | L-3 Communications Security And Detection Systems, Inc. | 3D mapping with two orthogonal imaging views |
US9042634B2 (en) * | 2013-01-15 | 2015-05-26 | General Electric Company | Method system and computer product for non-destructive object analysis |
CN103961135B (zh) * | 2013-02-04 | 2017-04-12 | 通用电气公司 | 用于侦测三维超声图像中导管位置的***及方法 |
CN110264833A (zh) * | 2013-03-11 | 2019-09-20 | 林肯环球股份有限公司 | 在实时仿真的虚拟现实焊接环境中提供增强的使用者体验的***和方法 |
US9349220B2 (en) * | 2013-03-12 | 2016-05-24 | Kabushiki Kaisha Toshiba | Curve correction in volume data sets |
US9600895B2 (en) * | 2013-05-02 | 2017-03-21 | Saso Koceski | System and method for three-dimensional nerve segmentation using magnetic resonance imaging |
CN103284694B (zh) * | 2013-05-22 | 2015-01-21 | 西安电子科技大学 | 一种活体动物血管新生定量分析方法 |
US9974442B2 (en) * | 2013-06-24 | 2018-05-22 | Toshiba Medical Systems Corporation | Method of, and apparatus for, processing volumetric image data |
EP3035884B1 (en) * | 2013-08-13 | 2022-11-23 | Regents of the University of Minnesota | Computer visualization of anatomical items |
DE102013220539A1 (de) * | 2013-10-11 | 2015-04-16 | Siemens Aktiengesellschaft | Modifikation einer Hohlorgan-Repräsentation |
JP6415927B2 (ja) * | 2013-11-08 | 2018-10-31 | キヤノンメディカルシステムズ株式会社 | 医用画像処理装置、x線コンピュータ断層撮影装置、および医用画像処理プログラム |
KR101578770B1 (ko) * | 2013-11-21 | 2015-12-18 | 삼성전자주식회사 | 의료 영상 처리 장치 및 그에 따른 의료 영상 처리 방법 |
KR101660370B1 (ko) | 2013-12-12 | 2016-09-27 | 삼성메디슨 주식회사 | 초음파 영상 표시 방법 및 장치 |
JP5857367B2 (ja) * | 2013-12-26 | 2016-02-10 | 株式会社Aze | 医用画像表示制御装置、方法およびプログラム |
JP6243763B2 (ja) * | 2014-03-14 | 2017-12-06 | テルモ株式会社 | 画像処理装置、画像処理装置の作動方法、及びプログラム |
US8917925B1 (en) * | 2014-03-28 | 2014-12-23 | Heartflow, Inc. | Systems and methods for data and model-driven image reconstruction and enhancement |
JP6382050B2 (ja) * | 2014-09-29 | 2018-08-29 | キヤノンメディカルシステムズ株式会社 | 医用画像診断装置、画像処理装置、画像処理方法及び画像処理プログラム |
WO2016067260A1 (en) * | 2014-10-30 | 2016-05-06 | Koninklijke Philips N.V. | Ultrasound visualization of curved structures |
EP3245632B1 (en) * | 2015-01-16 | 2020-07-15 | Koninklijke Philips N.V. | Vessel lumen sub-resolution segmentation |
JP6476041B2 (ja) | 2015-03-31 | 2019-02-27 | 株式会社Aze | 医用画像診断装置、その制御方法、及びプログラム |
KR101911396B1 (ko) | 2015-06-18 | 2018-12-20 | 연세대학교 산학협력단 | 혈관의 굽힘도 결정방법 |
JP6517953B2 (ja) * | 2015-06-29 | 2019-05-22 | コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. | インタラクティブ・メッシュ編集システム及び方法 |
JP6544092B2 (ja) * | 2015-07-08 | 2019-07-17 | 国立大学法人東京農工大学 | 血管径測定装置 |
JP5890055B1 (ja) * | 2015-07-09 | 2016-03-22 | 株式会社アルム | 血管画像処理装置、血管画像処理プログラム、および血管画像処理方法 |
JP6565422B2 (ja) | 2015-07-24 | 2019-08-28 | 富士通株式会社 | 画像処理プログラム、画像処理装置及び画像処理方法 |
US10603004B2 (en) * | 2015-07-27 | 2020-03-31 | Koninklijke Philips N.V. | Revascularisation localisation and pre and post quantitative coronary angiography |
JP6613903B2 (ja) * | 2016-01-12 | 2019-12-04 | 株式会社島津製作所 | イメージング装置 |
CA2958003C (en) * | 2016-02-19 | 2022-04-05 | Paul Stanley Addison | System and methods for video-based monitoring of vital signs |
JP6792340B2 (ja) * | 2016-03-29 | 2020-11-25 | ザイオソフト株式会社 | 医用画像処理装置、医用画像処理方法、及び医用画像処理プログラム |
JP6677113B2 (ja) * | 2016-07-19 | 2020-04-08 | 富士通株式会社 | 電子機器の製造装置、及びケーブル形状推定プログラム |
US10853948B2 (en) * | 2016-08-10 | 2020-12-01 | Agfa Healthcare Gmbh | Method for automatically detecting systemic arteries in arbitrary field-of-view computed tomography angiography (CTA) |
EP3300021B1 (en) * | 2016-09-22 | 2018-12-05 | RaySearch Laboratories AB | Image processing system and method for interactive contouring of three-dimensional medical data |
JP6821153B2 (ja) * | 2016-11-10 | 2021-01-27 | 大日本印刷株式会社 | 生体組織画像解析システム、画像処理システム及びプログラム |
JP6871007B2 (ja) * | 2017-02-13 | 2021-05-12 | キヤノンメディカルシステムズ株式会社 | 医用画像処理装置及び医用画像診断システム |
CN108451540B (zh) * | 2017-02-17 | 2021-08-31 | 深圳先进技术研究院 | 一种血流储备分数测量方法和装置 |
WO2018175094A1 (en) * | 2017-03-21 | 2018-09-27 | Canon U.S.A., Inc. | Methods, apparatuses and storage mediums for ablation planning and performance |
US10475235B2 (en) * | 2017-03-29 | 2019-11-12 | Fujifilm Corporation | Three-dimensional image processing apparatus, three-dimensional image processing method, and three-dimensional image processing program |
JP7202595B2 (ja) * | 2017-05-31 | 2023-01-12 | 株式会社根本杏林堂 | 血管画像処理システムおよび血管画像処理方法 |
CN107451406A (zh) * | 2017-07-28 | 2017-12-08 | 海纳医信(北京)软件科技有限责任公司 | 血管分析方法、装置、存储介质和处理器 |
CN107296620B (zh) * | 2017-07-28 | 2020-10-16 | 海纳医信(北京)软件科技有限责任公司 | 主动脉检测方法、装置、存储介质和处理器 |
EP3654244A4 (en) | 2017-07-31 | 2020-11-04 | Shanghai United Imaging Healthcare Co., Ltd. | METHOD AND SYSTEM FOR EXTRACTING A REGION OF INTEREST FROM VOLUME DATA |
CN107468334B (zh) * | 2017-08-01 | 2019-07-16 | 强联智创(北京)科技有限公司 | 一种三维微导管塑形辅助设计***及设计方法 |
CN111182836A (zh) * | 2017-09-01 | 2020-05-19 | 佳能株式会社 | 信息处理装置、信息处理方法、信息处理***和程序 |
EP3457404A1 (en) * | 2017-09-18 | 2019-03-20 | Koninklijke Philips N.V. | Estimating flow to vessel bifurcations for simulated hemodynamics |
EP3681394A1 (en) | 2017-11-13 | 2020-07-22 | Covidien LP | Systems and methods for video-based monitoring of a patient |
JP7114252B2 (ja) * | 2017-12-28 | 2022-08-08 | キヤノンメディカルシステムズ株式会社 | 医用画像処理装置、その制御方法、及びプログラム |
WO2019152846A1 (en) * | 2018-02-02 | 2019-08-08 | Centerline Biomedical, Inc. | Graphical user interface for marking anatomic structures |
JP7037810B2 (ja) * | 2018-03-05 | 2022-03-17 | 国立大学法人山口大学 | 画像処理装置と画像処理プログラムと画像処理方法 |
CN108564568A (zh) * | 2018-03-23 | 2018-09-21 | 沈阳东软医疗***有限公司 | 冠脉的显示方法、装置、设备及存储介质 |
WO2019197848A1 (en) * | 2018-04-13 | 2019-10-17 | Motilent Ltd. | Image analysis method |
KR101973513B1 (ko) | 2018-05-14 | 2019-04-30 | 주식회사 코어라인소프트 | 생체 내 관의 대표값 측정 방법 및 시스템 |
CN109035353B (zh) * | 2018-06-27 | 2022-09-20 | 河南科技大学 | 一种基于ct图像多平面重建的血管拉直曲面重组方法 |
CN113012108B (zh) * | 2018-07-24 | 2024-02-20 | 上海博动医疗科技股份有限公司 | 血管图像的处理方法、装置及成像设备 |
CN112584753A (zh) | 2018-08-09 | 2021-03-30 | 柯惠有限合伙公司 | 基于视频的患者监测***以及用于检测和监测呼吸的相关方法 |
JP7238319B2 (ja) | 2018-10-10 | 2023-03-14 | 株式会社ニコン | 画像処理方法、画像処理装置、画像処理プログラム、及び血管径算出装置 |
JP7048760B2 (ja) * | 2018-10-31 | 2022-04-05 | 富士フイルム株式会社 | 領域修正装置、方法およびプログラム |
WO2020097425A2 (en) * | 2018-11-09 | 2020-05-14 | Vida Diagnostics, Inc. | Cut-surface display of tubular structures |
US11315275B2 (en) | 2019-01-28 | 2022-04-26 | Covidien Lp | Edge handling methods for associated depth sensing camera devices, systems, and methods |
CN110111429B (zh) * | 2019-03-16 | 2022-11-18 | 哈尔滨理工大学 | 一种检测单像素血管的方法 |
JP7127212B2 (ja) * | 2019-04-25 | 2022-08-29 | 富士フイルム株式会社 | 画像の向き設定装置、方法およびプログラム |
CN110675481B (zh) * | 2019-09-26 | 2020-07-17 | 慧影医疗科技(北京)有限公司 | 影像交互联动方法、装置及可读存储介质 |
CN112164020B (zh) * | 2020-03-31 | 2024-01-23 | 苏州润迈德医疗科技有限公司 | 精确提取血管中心线的方法、装置、分析***和存储介质 |
WO2021207289A1 (en) | 2020-04-07 | 2021-10-14 | Vida Diagnostics, Inc. | Subject specific coordinatization and virtual navigation systems and methods |
EP4147643A4 (en) * | 2020-05-07 | 2024-04-24 | Imed Technologies, Inc. | IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD, PROGRAM AND IMAGE PROCESSING SYSTEM |
KR102399510B1 (ko) * | 2020-06-02 | 2022-05-19 | 주식회사 메디픽셀 | 사용자 입력에 기초하여 혈관 영상을 처리하는 방법 및 장치 |
KR102395873B1 (ko) | 2020-06-02 | 2022-05-10 | 주식회사 메디픽셀 | 자동으로 혈관 영상을 처리하는 방법 및 장치 |
CN112138249B (zh) * | 2020-08-24 | 2022-02-18 | 同济大学 | 一种基于超声评估的静脉注射机器人控制方法 |
KR102583135B1 (ko) * | 2021-11-04 | 2023-09-27 | 오스템임플란트 주식회사 | 교정 진단을 위해 서로 다른 시점에 획득된 복수개의 이미지를 중첩하여 디스플레이하는 방법, 디바이스 및 그 기록매체 |
JP7500091B2 (ja) | 2022-07-21 | 2024-06-17 | 株式会社マックスネット | 脳動脈瘤の瘤ネック平面の生成方法とコンピュータプログラム |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5734384A (en) * | 1991-11-29 | 1998-03-31 | Picker International, Inc. | Cross-referenced sectioning and reprojection of diagnostic image volumes |
US5891030A (en) | 1997-01-24 | 1999-04-06 | Mayo Foundation For Medical Education And Research | System for two dimensional and three dimensional imaging of tubular structures in the human body |
WO1999042977A1 (en) | 1998-02-23 | 1999-08-26 | Algotec Systems Ltd. | Automatic path planning system and method |
JPH11318884A (ja) | 1998-03-09 | 1999-11-24 | Hitachi Medical Corp | 画像表示装置 |
WO2001037219A1 (en) | 1999-11-19 | 2001-05-25 | General Electric Company | Method and apparatus for reformatting tubular volumetric bodies |
US6690816B2 (en) * | 2000-04-07 | 2004-02-10 | The University Of North Carolina At Chapel Hill | Systems and methods for tubular object processing |
US20040223636A1 (en) * | 1999-11-19 | 2004-11-11 | Edic Peter Michael | Feature quantification from multidimensional image data |
US20050245803A1 (en) * | 2002-03-14 | 2005-11-03 | Glenn Jr William V | System and method for analyzing and displaying computed tomography data |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1274898A (zh) * | 2000-04-30 | 2000-11-29 | 重庆炜迪科技发展有限公司 | 一种获取三维透明x数字图像的方法 |
US6643533B2 (en) * | 2000-11-28 | 2003-11-04 | Ge Medical Systems Global Technology Company, Llc | Method and apparatus for displaying images of tubular structures |
-
2003
- 2003-03-20 JP JP2003079117A patent/JP4421203B2/ja not_active Expired - Fee Related
-
2004
- 2004-03-19 US US10/803,930 patent/US7369691B2/en not_active Expired - Fee Related
- 2004-03-22 CN CNB2004100631043A patent/CN100343857C/zh not_active Expired - Fee Related
- 2004-03-22 CN CNB2006101630189A patent/CN100545873C/zh not_active Expired - Fee Related
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5734384A (en) * | 1991-11-29 | 1998-03-31 | Picker International, Inc. | Cross-referenced sectioning and reprojection of diagnostic image volumes |
US5891030A (en) | 1997-01-24 | 1999-04-06 | Mayo Foundation For Medical Education And Research | System for two dimensional and three dimensional imaging of tubular structures in the human body |
WO1999042977A1 (en) | 1998-02-23 | 1999-08-26 | Algotec Systems Ltd. | Automatic path planning system and method |
JP2002504385A (ja) | 1998-02-23 | 2002-02-12 | アルゴテック システムズ リミテッド | 自動経路立案方法 |
JPH11318884A (ja) | 1998-03-09 | 1999-11-24 | Hitachi Medical Corp | 画像表示装置 |
WO2001037219A1 (en) | 1999-11-19 | 2001-05-25 | General Electric Company | Method and apparatus for reformatting tubular volumetric bodies |
JP2003514600A (ja) | 1999-11-19 | 2003-04-22 | ゼネラル・エレクトリック・カンパニイ | 管状のボリュメトリック物体を再フォーマットするための方法及び装置 |
US20040223636A1 (en) * | 1999-11-19 | 2004-11-11 | Edic Peter Michael | Feature quantification from multidimensional image data |
US6690816B2 (en) * | 2000-04-07 | 2004-02-10 | The University Of North Carolina At Chapel Hill | Systems and methods for tubular object processing |
US20050245803A1 (en) * | 2002-03-14 | 2005-11-03 | Glenn Jr William V | System and method for analyzing and displaying computed tomography data |
Cited By (218)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20060043264A1 (en) * | 2004-09-02 | 2006-03-02 | Casio Computer Co., Ltd. | Imaging apparatus, image processing method for imaging apparatus, recording medium and carrier wave signal |
US7643701B2 (en) * | 2004-09-02 | 2010-01-05 | Casio Computer Co., Ltd. | Imaging apparatus for correcting a distortion of an image |
US20070293755A1 (en) * | 2004-09-22 | 2007-12-20 | Takashi Shirahata | Medical Image Display Device, Method, and Program |
US7801346B2 (en) * | 2004-09-24 | 2010-09-21 | Hitachi Medical Corporation | Medical image display device, method, and program |
US20090005693A1 (en) * | 2004-12-22 | 2009-01-01 | Biotree Systems, Inc. | Medical Imaging Methods and Apparatus for Diagnosis and Monitoring of Diseases and Uses Therefor |
US20080205728A1 (en) * | 2005-03-09 | 2008-08-28 | Koninklijke Philips Electronics, N.V. | Apparatus and Method for Providing 2D Representation of 3D Image Data Representing an Anatomical Lumen Tree Structure |
US8019135B2 (en) * | 2005-03-09 | 2011-09-13 | Koninklijke Philips Electronics N. V. | Apparatus and method for providing 2D representation of 3D image data representing an anatomical lumen tree structure |
US20090168954A1 (en) * | 2005-05-20 | 2009-07-02 | Omid Ebrahimi Kia | Method and apparatus for generating a panoramic image by combining image data generated from multiple perspectives |
US20070014461A1 (en) * | 2005-05-20 | 2007-01-18 | Imaging Sciences International, Inc. | Location of curved structure |
US7783093B2 (en) | 2005-05-20 | 2010-08-24 | Imaging Sciences International Llc | Method for locating a curved object |
US7946987B2 (en) * | 2005-07-20 | 2011-05-24 | Panasonic Corporation | Ultrasonic diagnostic apparatus |
US20090118615A1 (en) * | 2005-07-20 | 2009-05-07 | Matsushita Electric Industrial Co., Ltd. | Ultrasonic diagnostic apparatus |
US20070073147A1 (en) * | 2005-09-28 | 2007-03-29 | Siemens Medical Solutions Usa, Inc. | Method and apparatus for displaying a measurement associated with an anatomical feature |
US20080025587A1 (en) * | 2006-07-17 | 2008-01-31 | Christian Asbeck | Method and apparatus for determining the spatial profile of a vessel axis in volume data records for medical imaging |
US7881512B2 (en) * | 2006-07-17 | 2011-02-01 | Siemens Aktiengesellschaft | Method and apparatus for determining the spatial profile of a vessel axis in volume data records for medical imaging |
US20080079722A1 (en) * | 2006-09-25 | 2008-04-03 | Siemens Corporate Research, Inc. | System and method for view-dependent cutout geometry for importance-driven volume rendering |
US7952592B2 (en) * | 2006-09-25 | 2011-05-31 | Siemens Medical Solutions Usa, Inc. | System and method for view-dependent cutout geometry for importance-driven volume rendering |
US8712117B2 (en) | 2006-09-29 | 2014-04-29 | Koninklijke Philips N.V. | Methods, systems, and computer program product for virtually modifying surface region curvature to detect protrusions |
US20110235882A1 (en) * | 2006-09-29 | 2011-09-29 | Koninklijke Philips Electronics N.V. | Methods, system and computer program product for detecting a protrusion |
US20080154137A1 (en) * | 2006-11-22 | 2008-06-26 | Celine Pruvot | Method, system, and computer product for separating coronary lumen, coronary vessel wall and calcified plaque in an intravascular ultrasound view |
US7993274B2 (en) * | 2006-11-22 | 2011-08-09 | General Electric Company | Method, system, and computer product for automatically extracting and tracking cardiac calcifications and determining a tracking centerline |
US20080119734A1 (en) * | 2006-11-22 | 2008-05-22 | Celine Pruvot | Method, system, and computer product for automatically extracting and tracking cardiac calcifications and determining a tracking centerline |
US11179038B2 (en) | 2007-03-08 | 2021-11-23 | Sync-Rx, Ltd | Automatic stabilization of a frames of image stream of a moving organ having intracardiac or intravascular tool in the organ that is displayed in movie format |
US10307061B2 (en) | 2007-03-08 | 2019-06-04 | Sync-Rx, Ltd. | Automatic tracking of a tool upon a vascular roadmap |
US20100220917A1 (en) * | 2007-03-08 | 2010-09-02 | Sync-Rx, Ltd. | Automatic generation of a vascular skeleton |
US9008754B2 (en) | 2007-03-08 | 2015-04-14 | Sync-Rx, Ltd. | Automatic correction and utilization of a vascular roadmap comprising a tool |
US20100171819A1 (en) * | 2007-03-08 | 2010-07-08 | Sync-Rx, Ltd. | Automatic reduction of interfering elements from an image stream of a moving organ |
US9008367B2 (en) | 2007-03-08 | 2015-04-14 | Sync-Rx, Ltd. | Apparatus and methods for reducing visibility of a periphery of an image stream |
US20100160773A1 (en) * | 2007-03-08 | 2010-06-24 | Sync-Rx, Ltd. | Automatic quantitative vessel analysis at the location of an automatically-detected tool |
US9014453B2 (en) | 2007-03-08 | 2015-04-21 | Sync-Rx, Ltd. | Automatic angiogram detection |
US8781193B2 (en) | 2007-03-08 | 2014-07-15 | Sync-Rx, Ltd. | Automatic quantitative vessel analysis |
US8463007B2 (en) * | 2007-03-08 | 2013-06-11 | Sync-Rx, Ltd. | Automatic generation of a vascular skeleton |
US9216065B2 (en) | 2007-03-08 | 2015-12-22 | Sync-Rx, Ltd. | Forming and displaying a composite image |
US9305334B2 (en) | 2007-03-08 | 2016-04-05 | Sync-Rx, Ltd. | Luminal background cleaning |
US10226178B2 (en) | 2007-03-08 | 2019-03-12 | Sync-Rx Ltd. | Automatic reduction of visibility of portions of an image |
US11064964B2 (en) | 2007-03-08 | 2021-07-20 | Sync-Rx, Ltd | Determining a characteristic of a lumen by measuring velocity of a contrast agent |
US9308052B2 (en) | 2007-03-08 | 2016-04-12 | Sync-Rx, Ltd. | Pre-deployment positioning of an implantable device within a moving organ |
US9968256B2 (en) | 2007-03-08 | 2018-05-15 | Sync-Rx Ltd. | Automatic identification of a tool |
US9375164B2 (en) | 2007-03-08 | 2016-06-28 | Sync-Rx, Ltd. | Co-use of endoluminal data and extraluminal imaging |
US9888969B2 (en) | 2007-03-08 | 2018-02-13 | Sync-Rx Ltd. | Automatic quantitative vessel analysis |
US8700130B2 (en) | 2007-03-08 | 2014-04-15 | Sync-Rx, Ltd. | Stepwise advancement of a medical tool |
US10499814B2 (en) | 2007-03-08 | 2019-12-10 | Sync-Rx, Ltd. | Automatic generation and utilization of a vascular roadmap |
US10716528B2 (en) | 2007-03-08 | 2020-07-21 | Sync-Rx, Ltd. | Automatic display of previously-acquired endoluminal images |
US9629571B2 (en) | 2007-03-08 | 2017-04-25 | Sync-Rx, Ltd. | Co-use of endoluminal data and extraluminal imaging |
US9717415B2 (en) | 2007-03-08 | 2017-08-01 | Sync-Rx, Ltd. | Automatic quantitative vessel analysis at the location of an automatically-detected tool |
US9855384B2 (en) | 2007-03-08 | 2018-01-02 | Sync-Rx, Ltd. | Automatic enhancement of an image stream of a moving organ and displaying as a movie |
US11197651B2 (en) | 2007-03-08 | 2021-12-14 | Sync-Rx, Ltd. | Identification and presentation of device-to-vessel relative motion |
US8542900B2 (en) | 2007-03-08 | 2013-09-24 | Sync-Rx Ltd. | Automatic reduction of interfering elements from an image stream of a moving organ |
US8170328B2 (en) * | 2007-04-12 | 2012-05-01 | Fujifilm Corporation | Image display method, apparatus, and program |
US20080253630A1 (en) * | 2007-04-12 | 2008-10-16 | Fujifilm Corporation | Image display method, apparatus, and program |
US8447082B2 (en) * | 2007-06-11 | 2013-05-21 | Hitachi Medical Corporation | Medical image displaying apparatus, medical image displaying method, and medical image displaying program |
US20100215228A1 (en) * | 2007-06-11 | 2010-08-26 | Hitachi Medical Corporation | Medical image displaying apparatus, medical image displaying method, and medical image displaying program |
US20090016483A1 (en) * | 2007-07-10 | 2009-01-15 | Kabushiki Kaisha Toshiba | X-ray apparatus, image processing display apparatus and computer program product |
US8064667B2 (en) | 2007-07-10 | 2011-11-22 | Kabushiki Kaisha Toshiba | X-ray apparatus, image processing display apparatus and computer program product |
US20090310847A1 (en) * | 2008-03-25 | 2009-12-17 | Takeo Matsuzaki | Medical image processing apparatus and x-ray diagnosis apparatus |
US8542891B2 (en) | 2008-07-04 | 2013-09-24 | Kabushiki Kaisha Toshiba | X-ray imaging apparatus that displays analysis image with taken image, X-ray imaging method, and image processing apparatus |
US20100002839A1 (en) * | 2008-07-04 | 2010-01-07 | Kabushiki Kaisha Toshiba | X-ray imaging apparatus that displays analysis image with taken image, x-ray imaging method, and image processing apparatus |
US11107587B2 (en) | 2008-07-21 | 2021-08-31 | The Board Of Trustees Of The Leland Stanford Junior University | Method for tuning patient-specific cardiovascular simulations |
US8200466B2 (en) | 2008-07-21 | 2012-06-12 | The Board Of Trustees Of The Leland Stanford Junior University | Method for tuning patient-specific cardiovascular simulations |
US8437520B2 (en) * | 2008-10-10 | 2013-05-07 | Kabushiki Kaisha Toshiba | Medical image processor and medical image processing method |
US20100092053A1 (en) * | 2008-10-10 | 2010-04-15 | Kabushiki Kaisha Toshiba | Medical image processor and medical image processing method |
US9095313B2 (en) | 2008-11-18 | 2015-08-04 | Sync-Rx, Ltd. | Accounting for non-uniform longitudinal motion during movement of an endoluminal imaging probe |
US9974509B2 (en) | 2008-11-18 | 2018-05-22 | Sync-Rx Ltd. | Image super enhancement |
US11883149B2 (en) | 2008-11-18 | 2024-01-30 | Sync-Rx Ltd. | Apparatus and methods for mapping a sequence of images to a roadmap image |
US10362962B2 (en) | 2008-11-18 | 2019-07-30 | Synx-Rx, Ltd. | Accounting for skipped imaging locations during movement of an endoluminal imaging probe |
US11064903B2 (en) | 2008-11-18 | 2021-07-20 | Sync-Rx, Ltd | Apparatus and methods for mapping a sequence of images to a roadmap image |
US9144394B2 (en) | 2008-11-18 | 2015-09-29 | Sync-Rx, Ltd. | Apparatus and methods for determining a plurality of local calibration factors for an image |
US8855744B2 (en) | 2008-11-18 | 2014-10-07 | Sync-Rx, Ltd. | Displaying a device within an endoluminal image stack |
US9101286B2 (en) | 2008-11-18 | 2015-08-11 | Sync-Rx, Ltd. | Apparatus and methods for determining a dimension of a portion of a stack of endoluminal data points |
US20100128963A1 (en) * | 2008-11-21 | 2010-05-27 | Kabushiki Kaisha Toshiba | Image processing apparatus and image processing method |
US9788729B2 (en) * | 2008-11-21 | 2017-10-17 | Toshiba Medical Systems Corporation | Image processing apparatus and image processing method |
US8594399B2 (en) * | 2009-01-30 | 2013-11-26 | Siemens Aktiengesellschaft | Method for actuating an image output device, method for determining tangential slice planes, actuation module and slice plane determination unit |
US20100195879A1 (en) * | 2009-01-30 | 2010-08-05 | Bernhardt Dominik | Method for actuating an image output device, method for determining tangential slice planes, actuation module and slice plane determination unit |
US10354050B2 (en) | 2009-03-17 | 2019-07-16 | The Board Of Trustees Of Leland Stanford Junior University | Image processing method for determining patient-specific cardiovascular information |
EP2484285A4 (en) * | 2009-09-30 | 2014-05-14 | Fujifilm Corp | DIAGNOSTIC ASSISTING SYSTEM, DIAGNOSTIC ASSISTING PROGRAM, AND DIAGNOSTIC ASSISTING METHOD |
US8744151B2 (en) | 2009-09-30 | 2014-06-03 | Fujifilm Corporation | Diagnosis assisting system, diagnosis assisting program and diagnosis assisting method |
EP2484285A1 (en) * | 2009-09-30 | 2012-08-08 | FUJIFILM Corporation | Diagnosis assisting system, diagnosis assisting program, and diagnosis assisting method |
CN102098437A (zh) * | 2009-11-19 | 2011-06-15 | 微软公司 | 集成取景器和数字媒体 |
US20110119619A1 (en) * | 2009-11-19 | 2011-05-19 | Microsoft Corporation | Integrated viewfinder and digital media |
CN102098437B (zh) * | 2009-11-19 | 2016-06-29 | 微软技术许可有限责任公司 | 集成取景器和数字媒体 |
US8239783B2 (en) * | 2009-11-19 | 2012-08-07 | Microsoft Corporation | Integrated viewfinder and digital media |
US8934686B2 (en) | 2009-11-26 | 2015-01-13 | Algotec Systems Ltd. | User interface for selecting paths in an image |
US20110135175A1 (en) * | 2009-11-26 | 2011-06-09 | Algotec Systems Ltd. | User interface for selecting paths in an image |
US20110170758A1 (en) * | 2010-01-12 | 2011-07-14 | Fujifilm Corporation | Tomographic image generating apparatus, tomographic image generating method, and program for generating tomographic images |
US9445777B2 (en) | 2010-03-31 | 2016-09-20 | Fujifilm Corporation | Projection image generation apparatus, program and method |
US9865079B2 (en) | 2010-03-31 | 2018-01-09 | Fujifilm Corporation | Virtual endoscopic image generated using an opacity curve |
US8144147B2 (en) * | 2010-04-07 | 2012-03-27 | Intel Corporation | Hierarchical bounding of displaced parametric surfaces |
US20120154399A1 (en) * | 2010-04-07 | 2012-06-21 | Jacob Munkberg | Hierarchical Bounding of Displaced Parametric Surfaces |
CN102214369B (zh) * | 2010-04-07 | 2014-03-05 | 英特尔公司 | 移位参数曲面的分层包围 |
CN102214369A (zh) * | 2010-04-07 | 2011-10-12 | 英特尔公司 | 移位参数曲面的分层包围 |
US9424680B2 (en) * | 2010-04-16 | 2016-08-23 | Koninklijke Philips N.V. | Image data reformatting |
US20130064440A1 (en) * | 2010-04-16 | 2013-03-14 | Koninklijke Philips Electronics N.V. | Image data reformatting |
US20120026162A1 (en) * | 2010-07-28 | 2012-02-02 | Fujifilm Corporation | Diagnosis assisting apparatus, diagnosis assisting program, and diagnosis assisting method |
US8994720B2 (en) * | 2010-07-28 | 2015-03-31 | Fujifilm Corporation | Diagnosis assisting apparatus, diagnosis assisting program, and diagnosis assisting method |
US9149197B2 (en) | 2010-08-12 | 2015-10-06 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US8311748B2 (en) | 2010-08-12 | 2012-11-13 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US12029494B2 (en) | 2010-08-12 | 2024-07-09 | Heartflow, Inc. | Method and system for image processing to determine blood flow |
US12016635B2 (en) | 2010-08-12 | 2024-06-25 | Heartflow, Inc. | Method and system for image processing to determine blood flow |
US8157742B2 (en) | 2010-08-12 | 2012-04-17 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US11793575B2 (en) | 2010-08-12 | 2023-10-24 | Heartflow, Inc. | Method and system for image processing to determine blood flow |
US11583340B2 (en) | 2010-08-12 | 2023-02-21 | Heartflow, Inc. | Method and system for image processing to determine blood flow |
US9078564B2 (en) | 2010-08-12 | 2015-07-14 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US9081882B2 (en) | 2010-08-12 | 2015-07-14 | HeartFlow, Inc | Method and system for patient-specific modeling of blood flow |
US11298187B2 (en) | 2010-08-12 | 2022-04-12 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US8812246B2 (en) | 2010-08-12 | 2014-08-19 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US8249815B2 (en) | 2010-08-12 | 2012-08-21 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US8812245B2 (en) | 2010-08-12 | 2014-08-19 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US9152757B2 (en) | 2010-08-12 | 2015-10-06 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US8311747B2 (en) | 2010-08-12 | 2012-11-13 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US11154361B2 (en) | 2010-08-12 | 2021-10-26 | Heartflow, Inc. | Method and system for image processing to determine blood flow |
US9167974B2 (en) | 2010-08-12 | 2015-10-27 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US11135012B2 (en) | 2010-08-12 | 2021-10-05 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US9226672B2 (en) | 2010-08-12 | 2016-01-05 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US9235679B2 (en) | 2010-08-12 | 2016-01-12 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US9268902B2 (en) | 2010-08-12 | 2016-02-23 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US9271657B2 (en) | 2010-08-12 | 2016-03-01 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US11116575B2 (en) | 2010-08-12 | 2021-09-14 | Heartflow, Inc. | Method and system for image processing to determine blood flow |
US8311750B2 (en) | 2010-08-12 | 2012-11-13 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US11090118B2 (en) | 2010-08-12 | 2021-08-17 | Heartflow, Inc. | Method and system for image processing and patient-specific modeling of blood flow |
US11083524B2 (en) | 2010-08-12 | 2021-08-10 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US8315814B2 (en) | 2010-08-12 | 2012-11-20 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US8734357B2 (en) | 2010-08-12 | 2014-05-27 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US11033332B2 (en) | 2010-08-12 | 2021-06-15 | Heartflow, Inc. | Method and system for image processing to determine blood flow |
US8734356B2 (en) | 2010-08-12 | 2014-05-27 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US8315813B2 (en) | 2010-08-12 | 2012-11-20 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US10702339B2 (en) | 2010-08-12 | 2020-07-07 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US10702340B2 (en) | 2010-08-12 | 2020-07-07 | Heartflow, Inc. | Image processing and patient-specific modeling of blood flow |
US9449147B2 (en) | 2010-08-12 | 2016-09-20 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US10682180B2 (en) | 2010-08-12 | 2020-06-16 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US10531923B2 (en) | 2010-08-12 | 2020-01-14 | Heartflow, Inc. | Method and system for image processing to determine blood flow |
US8315812B2 (en) | 2010-08-12 | 2012-11-20 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US9585723B2 (en) | 2010-08-12 | 2017-03-07 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US10492866B2 (en) | 2010-08-12 | 2019-12-03 | Heartflow, Inc. | Method and system for image processing to determine blood flow |
US10478252B2 (en) | 2010-08-12 | 2019-11-19 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US9697330B2 (en) | 2010-08-12 | 2017-07-04 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US9706925B2 (en) | 2010-08-12 | 2017-07-18 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US8630812B2 (en) | 2010-08-12 | 2014-01-14 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US10441361B2 (en) | 2010-08-12 | 2019-10-15 | Heartflow, Inc. | Method and system for image processing and patient-specific modeling of blood flow |
US9743835B2 (en) | 2010-08-12 | 2017-08-29 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US8606530B2 (en) | 2010-08-12 | 2013-12-10 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US9801689B2 (en) | 2010-08-12 | 2017-10-31 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US9839484B2 (en) | 2010-08-12 | 2017-12-12 | Heartflow, Inc. | Method and system for image processing and patient-specific modeling of blood flow |
US9855105B2 (en) | 2010-08-12 | 2018-01-02 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US8594950B2 (en) | 2010-08-12 | 2013-11-26 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US10376317B2 (en) | 2010-08-12 | 2019-08-13 | Heartflow, Inc. | Method and system for image processing and patient-specific modeling of blood flow |
US9861284B2 (en) | 2010-08-12 | 2018-01-09 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US8523779B2 (en) | 2010-08-12 | 2013-09-03 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US9888971B2 (en) | 2010-08-12 | 2018-02-13 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US8321150B2 (en) | 2010-08-12 | 2012-11-27 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US8496594B2 (en) | 2010-08-12 | 2013-07-30 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US8386188B2 (en) | 2010-08-12 | 2013-02-26 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US10052158B2 (en) | 2010-08-12 | 2018-08-21 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US10080613B2 (en) | 2010-08-12 | 2018-09-25 | Heartflow, Inc. | Systems and methods for determining and visualizing perfusion of myocardial muscle |
US10080614B2 (en) | 2010-08-12 | 2018-09-25 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US10092360B2 (en) | 2010-08-12 | 2018-10-09 | Heartflow, Inc. | Method and system for image processing and patient-specific modeling of blood flow |
US10149723B2 (en) | 2010-08-12 | 2018-12-11 | Heartflow, Inc. | Method and system for image processing and patient-specific modeling of blood flow |
US10154883B2 (en) | 2010-08-12 | 2018-12-18 | Heartflow, Inc. | Method and system for image processing and patient-specific modeling of blood flow |
US10159529B2 (en) | 2010-08-12 | 2018-12-25 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US10166077B2 (en) | 2010-08-12 | 2019-01-01 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US10179030B2 (en) | 2010-08-12 | 2019-01-15 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US10327847B2 (en) | 2010-08-12 | 2019-06-25 | Heartflow, Inc. | Method and system for patient-specific modeling of blood flow |
US10321958B2 (en) | 2010-08-12 | 2019-06-18 | Heartflow, Inc. | Method and system for image processing to determine patient-specific blood flow characteristics |
US8761474B2 (en) * | 2011-07-25 | 2014-06-24 | Siemens Aktiengesellschaft | Method for vascular flow pattern analysis |
US20130051640A1 (en) * | 2011-07-25 | 2013-02-28 | Siemens Corporation | Method for vascular flow pattern analysis |
US8755576B2 (en) * | 2011-09-09 | 2014-06-17 | Calgary Scientific Inc. | Determining contours of a vessel using an active contouring model |
US20130064435A1 (en) * | 2011-09-09 | 2013-03-14 | Calgary Scientific Inc. | Determining contours of a vessel using an active contouring model |
US10535189B2 (en) | 2011-09-09 | 2020-01-14 | Calgary Scientific Inc. | Image display of a centerline of tubular structure |
US9443303B2 (en) | 2011-09-09 | 2016-09-13 | Calgary Scientific Inc. | Image display of a centerline of tubular structure |
US9443317B2 (en) | 2011-09-09 | 2016-09-13 | Calgary Scientific Inc. | Image display of a centerline of tubular structure |
US9117141B2 (en) | 2011-10-14 | 2015-08-25 | Siemens Medical Solutions Usa, Inc. | Method and apparatus for identifying regions of interest in medical imaging data |
US9357980B2 (en) | 2012-01-10 | 2016-06-07 | Konica Minolta, Inc. | Ultrasound diagnostic apparatus and method for identifying blood vessel |
US20130216119A1 (en) * | 2012-02-17 | 2013-08-22 | Siemens Medical Solutions Usa, Inc. | System for Suppressing Vascular Structure in Medical Images |
US8848996B2 (en) * | 2012-02-17 | 2014-09-30 | Siemens Medical Solutions Usa, Inc. | System for suppressing vascular structure in medical images |
US8760557B2 (en) | 2012-02-24 | 2014-06-24 | Blackberry Limited | User interface for a digital camera |
US8675113B2 (en) | 2012-02-24 | 2014-03-18 | Research In Motion Limited | User interface for a digital camera |
US9390497B2 (en) | 2012-03-09 | 2016-07-12 | Fujifilm Corporation | Medical image processing apparatus, method and program |
US8706457B2 (en) | 2012-05-14 | 2014-04-22 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US9063634B2 (en) | 2012-05-14 | 2015-06-23 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US9517040B2 (en) | 2012-05-14 | 2016-12-13 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US8548778B1 (en) | 2012-05-14 | 2013-10-01 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US10842568B2 (en) | 2012-05-14 | 2020-11-24 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US9168012B2 (en) | 2012-05-14 | 2015-10-27 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US8914264B1 (en) | 2012-05-14 | 2014-12-16 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US8768669B1 (en) | 2012-05-14 | 2014-07-01 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US8855984B2 (en) | 2012-05-14 | 2014-10-07 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US9002690B2 (en) | 2012-05-14 | 2015-04-07 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US8768670B1 (en) | 2012-05-14 | 2014-07-01 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US11826106B2 (en) | 2012-05-14 | 2023-11-28 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US9063635B2 (en) | 2012-05-14 | 2015-06-23 | Heartflow, Inc. | Method and system for providing information from a patient-specific model of blood flow |
US10984531B2 (en) | 2012-06-26 | 2021-04-20 | Sync-Rx, Ltd. | Determining a luminal-flow-related index using blood velocity determination |
US10748289B2 (en) | 2012-06-26 | 2020-08-18 | Sync-Rx, Ltd | Coregistration of endoluminal data points with values of a luminal-flow-related index |
US9558589B2 (en) | 2012-09-12 | 2017-01-31 | Fujifilm Corporation | Medical image display apparatus, method, and program |
US11707196B2 (en) | 2012-10-24 | 2023-07-25 | Cathworks Ltd. | Automated measurement system and method for coronary artery disease scoring |
US11728037B2 (en) | 2012-10-24 | 2023-08-15 | Cathworks Ltd. | Diagnostically useful results in real time |
US11406337B2 (en) | 2012-10-24 | 2022-08-09 | Cathworks Ltd. | Calculating a fractional flow reserve |
US11615894B2 (en) | 2012-10-24 | 2023-03-28 | CathWorks, LTD. | Diagnostically useful results in real time |
US11278208B2 (en) | 2012-10-24 | 2022-03-22 | Cathworks Ltd. | Automated measurement system and method for coronary artery disease scoring |
US11295864B2 (en) | 2012-10-24 | 2022-04-05 | Cath Works Ltd. | Creating a vascular tree model |
US11081237B2 (en) | 2012-10-24 | 2021-08-03 | Cathworks Ltd. | Diagnostically useful results in real time |
US9734578B2 (en) * | 2013-05-13 | 2017-08-15 | Toshiba Medical Systems Corporation | Medical image analyzer |
US20160140712A1 (en) * | 2013-05-13 | 2016-05-19 | Kabushiki Kaisha Toshiba | Medical image analyzer |
US10007420B2 (en) * | 2013-09-17 | 2018-06-26 | Samsung Electronics Co., Ltd. | Method for processing data and electronic device thereof |
US20150082153A1 (en) * | 2013-09-17 | 2015-03-19 | Samsung Electronics Co., Ltd. | Method for processing data and electronic device thereof |
US11816837B2 (en) | 2013-10-24 | 2023-11-14 | Cathworks Ltd. | Vascular characteristic determination with correspondence modeling of a vascular tree |
US11138733B2 (en) | 2013-10-24 | 2021-10-05 | Cathworks Ltd. | Vascular characteristic determination with correspondence modeling of a vascular tree |
US20170032523A1 (en) * | 2014-04-10 | 2017-02-02 | Sync-Rx, Ltd | Image Analysis in the Presence of a Medical Device |
US20170071554A1 (en) * | 2015-09-16 | 2017-03-16 | Fujifilm Corporation | Tomographic image generation device, method and recording medium |
US10342499B2 (en) * | 2015-09-16 | 2019-07-09 | Fujifilm Corporation | Tomographic image generation device, method and recording medium |
US11160524B2 (en) | 2016-05-16 | 2021-11-02 | Cathworks Ltd. | Vascular path editing using energy function minimization |
US11666236B2 (en) | 2016-05-16 | 2023-06-06 | Cathworks Ltd. | System for vascular assessment |
US11076770B2 (en) | 2016-05-16 | 2021-08-03 | Cathworks Ltd. | System for vascular assessment |
US11937963B2 (en) | 2016-05-16 | 2024-03-26 | Cathworks Ltd. | Vascular selection from images |
US11004198B2 (en) | 2017-03-24 | 2021-05-11 | Pie Medical Imaging B.V. | Method and system for assessing vessel obstruction based on machine learning |
US11816836B2 (en) | 2018-04-11 | 2023-11-14 | Pie Medical Imaging B.V. | Method and system for assessing vessel obstruction based on machine learning |
US10699407B2 (en) * | 2018-04-11 | 2020-06-30 | Pie Medical Imaging B.V. | Method and system for assessing vessel obstruction based on machine learning |
US11599996B2 (en) | 2018-04-11 | 2023-03-07 | Pie Medical Imaging B.V. | Method and system for assessing vessel obstruction based on machine learning |
US12039685B2 (en) | 2019-09-23 | 2024-07-16 | Cathworks Ltd. | Methods, apparatus, and system for synchronization between a three-dimensional vascular model and an imaging device |
EP4064181A4 (en) * | 2019-11-19 | 2023-11-29 | Suzhou Rainmed Medical Technology Co., Ltd. | METHOD AND APPARATUS FOR ACQUIRING CONTOUR LINES OF A BLOOD VESSEL AS A FUNCTION OF A CENTRAL LINE OF A BLOOD VESSEL |
Also Published As
Publication number | Publication date |
---|---|
CN1551033A (zh) | 2004-12-01 |
CN1956010A (zh) | 2007-05-02 |
JP4421203B2 (ja) | 2010-02-24 |
JP2004283373A (ja) | 2004-10-14 |
CN100343857C (zh) | 2007-10-17 |
CN100545873C (zh) | 2009-09-30 |
US20040249270A1 (en) | 2004-12-09 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US7369691B2 (en) | Processor for analyzing tubular structure such as blood vessels | |
US6928314B1 (en) | System for two-dimensional and three-dimensional imaging of tubular structures in the human body | |
EP0964639B1 (en) | Method for two-dimensional and three-dimensional imaging of tubular structures in the human body | |
JP5129480B2 (ja) | 管状臓器の3次元再構成を行うシステム及び血管撮像装置の作動方法 | |
US6501848B1 (en) | Method and apparatus for three-dimensional reconstruction of coronary vessels from angiographic images and analytical techniques applied thereto | |
JP5078609B2 (ja) | 画像表示装置及びプログラム | |
US7890156B2 (en) | Medical image display method and apparatus | |
US8213699B2 (en) | Medical image processing apparatus and medical image diagnosis apparatus | |
EP2157905B1 (en) | A method for tracking 3d anatomical and pathological changes in tubular-shaped anatomical structures | |
JP4676021B2 (ja) | 診断支援装置、診断支援プログラムおよび診断支援方法 | |
CN113614845A (zh) | 动脉成像与评定***和方法以及相关的基于用户界面的工作流程 | |
JP5685605B2 (ja) | インターベンション装置をナビゲートするシステム及びその作動方法、コンピュータプログラムエレメント並びにコンピュータ可読媒体 | |
US8107701B2 (en) | Medical image display system and medical image display program | |
RU2466679C2 (ru) | Визуализация сосудистой структуры | |
WO1998032371A9 (en) | System for two-dimensional and three-dimensional imaging of tubular structures in the human body | |
JPH11128191A (ja) | 心臓内電気現象の診断装置およびその現象の表示方法 | |
JP2006246941A (ja) | 画像処理装置及び管走行トラッキング方法 | |
WO2006033113A2 (en) | Apparatus and method for fusion and in-operating-room presentation of volumetric data and 3-d angiographic data | |
JP2010528750A (ja) | 管状構造の検査 | |
RU2419882C2 (ru) | Способ визуализации секущих плоскостей для изогнутых продолговатых структур | |
JP2007044121A (ja) | 医用画像表示方法及び装置 | |
JP2004201873A (ja) | 画像処理方法及び画像処理装置並びにプログラム | |
JP2001087228A (ja) | 読影支援装置 | |
JP4318799B2 (ja) | 画像表示装置 | |
JP5159195B2 (ja) | 医用画像処理装置 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: TOSHIBA MEDICAL SYSTEMS CORPORATION, JAPAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KONDO, YASUHIRA;OHYU, SHIGEHARU;YAMAGATA, HITOSHI;AND OTHERS;REEL/FRAME:015664/0960 Effective date: 20040409 Owner name: KABUSHIKI KAISHA TOSHIBA, JAPAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KONDO, YASUHIRA;OHYU, SHIGEHARU;YAMAGATA, HITOSHI;AND OTHERS;REEL/FRAME:015664/0960 Effective date: 20040409 |
|
STCF | Information on status: patent grant |
Free format text: PATENTED CASE |
|
FPAY | Fee payment |
Year of fee payment: 4 |
|
FPAY | Fee payment |
Year of fee payment: 8 |
|
AS | Assignment |
Owner name: TOSHIBA MEDICAL SYSTEMS CORPORATION, JAPAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:KABUSHIKI KAISHA TOSHIBA;REEL/FRAME:038891/0693 Effective date: 20160316 |
|
FEPP | Fee payment procedure |
Free format text: MAINTENANCE FEE REMINDER MAILED (ORIGINAL EVENT CODE: REM.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY |
|
LAPS | Lapse for failure to pay maintenance fees |
Free format text: PATENT EXPIRED FOR FAILURE TO PAY MAINTENANCE FEES (ORIGINAL EVENT CODE: EXP.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY |
|
STCH | Information on status: patent discontinuation |
Free format text: PATENT EXPIRED DUE TO NONPAYMENT OF MAINTENANCE FEES UNDER 37 CFR 1.362 |
|
FP | Lapsed due to failure to pay maintenance fee |
Effective date: 20200506 |